#!/usr/bin/env node
"use strict";
/**
 * Strange Loops Extended MCP Server
 * Task-oriented agent tools for real-world problem solving
 */
var __assign = (this && this.__assign) || function () {
    __assign = Object.assign || function(t) {
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        }
        return t;
    };
    return __assign.apply(this, arguments);
};
var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
    return new (P || (P = Promise))(function (resolve, reject) {
        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
        step((generator = generator.apply(thisArg, _arguments || [])).next());
    });
};
var __generator = (this && this.__generator) || function (thisArg, body) {
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};
Object.defineProperty(exports, "__esModule", { value: true });
var index_js_1 = require("@modelcontextprotocol/sdk/server/index.js");
var stdio_js_1 = require("@modelcontextprotocol/sdk/server/stdio.js");
var types_js_1 = require("@modelcontextprotocol/sdk/types.js");
// Import our Strange Loop library
var StrangeLoop = require('../lib/strange-loop.js');
var StrangeLoopsExtendedMCPServer = /** @class */ (function () {
    function StrangeLoopsExtendedMCPServer() {
        this.isInitialized = false;
        this.activeTasks = new Map();
        this.swarms = new Map();
        this.taskCounter = 0;
        this.server = new index_js_1.Server({
            name: 'strange-loops-extended',
            version: '0.2.0',
        }, {
            capabilities: {
                tools: {},
            },
        });
        this.setupHandlers();
    }
    StrangeLoopsExtendedMCPServer.prototype.setupHandlers = function () {
        var _this = this;
        // List available tools
        this.server.setRequestHandler(types_js_1.ListToolsRequestSchema, function () { return __awaiter(_this, void 0, void 0, function () {
            return __generator(this, function (_a) {
                return [2 /*return*/, {
                        tools: this.getToolDefinitions()
                    }];
            });
        }); });
        // Handle tool calls
        this.server.setRequestHandler(types_js_1.CallToolRequestSchema, function (request) { return __awaiter(_this, void 0, void 0, function () {
            var _a, name, args, _b, error_1;
            return __generator(this, function (_c) {
                switch (_c.label) {
                    case 0: return [4 /*yield*/, this.ensureInitialized()];
                    case 1:
                        _c.sent();
                        _a = request.params, name = _a.name, args = _a.arguments;
                        _c.label = 2;
                    case 2:
                        _c.trys.push([2, 41, , 42]);
                        _b = name;
                        switch (_b) {
                            case 'agent_task_create': return [3 /*break*/, 3];
                            case 'agent_task_execute': return [3 /*break*/, 5];
                            case 'agent_task_status': return [3 /*break*/, 7];
                            case 'agent_task_results': return [3 /*break*/, 9];
                            case 'agent_search': return [3 /*break*/, 11];
                            case 'agent_analyze': return [3 /*break*/, 13];
                            case 'agent_optimize': return [3 /*break*/, 15];
                            case 'agent_monitor': return [3 /*break*/, 17];
                            case 'agent_predict': return [3 /*break*/, 19];
                            case 'agent_classify': return [3 /*break*/, 21];
                            case 'agent_generate': return [3 /*break*/, 23];
                            case 'agent_validate': return [3 /*break*/, 25];
                            case 'agent_coordinate': return [3 /*break*/, 27];
                            case 'agent_consensus': return [3 /*break*/, 29];
                            case 'agent_distribute': return [3 /*break*/, 31];
                            case 'agent_aggregate': return [3 /*break*/, 33];
                            case 'nano_swarm_create': return [3 /*break*/, 35];
                            case 'nano_swarm_run': return [3 /*break*/, 37];
                        }
                        return [3 /*break*/, 39];
                    case 3: return [4 /*yield*/, this.createAgentTask(args)];
                    case 4: return [2 /*return*/, _c.sent()];
                    case 5: return [4 /*yield*/, this.executeAgentTask(args)];
                    case 6: return [2 /*return*/, _c.sent()];
                    case 7: return [4 /*yield*/, this.getTaskStatus(args)];
                    case 8: return [2 /*return*/, _c.sent()];
                    case 9: return [4 /*yield*/, this.getTaskResults(args)];
                    case 10: return [2 /*return*/, _c.sent()];
                    case 11: return [4 /*yield*/, this.performAgentSearch(args)];
                    case 12: return [2 /*return*/, _c.sent()];
                    case 13: return [4 /*yield*/, this.performAgentAnalysis(args)];
                    case 14: return [2 /*return*/, _c.sent()];
                    case 15: return [4 /*yield*/, this.performOptimization(args)];
                    case 16: return [2 /*return*/, _c.sent()];
                    case 17: return [4 /*yield*/, this.performMonitoring(args)];
                    case 18: return [2 /*return*/, _c.sent()];
                    case 19: return [4 /*yield*/, this.performPrediction(args)];
                    case 20: return [2 /*return*/, _c.sent()];
                    case 21: return [4 /*yield*/, this.performClassification(args)];
                    case 22: return [2 /*return*/, _c.sent()];
                    case 23: return [4 /*yield*/, this.performGeneration(args)];
                    case 24: return [2 /*return*/, _c.sent()];
                    case 25: return [4 /*yield*/, this.performValidation(args)];
                    case 26: return [2 /*return*/, _c.sent()];
                    case 27: return [4 /*yield*/, this.coordinateAgents(args)];
                    case 28: return [2 /*return*/, _c.sent()];
                    case 29: return [4 /*yield*/, this.buildConsensus(args)];
                    case 30: return [2 /*return*/, _c.sent()];
                    case 31: return [4 /*yield*/, this.distributeWork(args)];
                    case 32: return [2 /*return*/, _c.sent()];
                    case 33: return [4 /*yield*/, this.aggregateResults(args)];
                    case 34: return [2 /*return*/, _c.sent()];
                    case 35: return [4 /*yield*/, this.createNanoSwarm(args)];
                    case 36: return [2 /*return*/, _c.sent()];
                    case 37: return [4 /*yield*/, this.runNanoSwarm(args)];
                    case 38: return [2 /*return*/, _c.sent()];
                    case 39: throw new Error("Unknown tool: ".concat(name));
                    case 40: return [3 /*break*/, 42];
                    case 41:
                        error_1 = _c.sent();
                        return [2 /*return*/, {
                                content: [
                                    {
                                        type: 'text',
                                        text: "Error: ".concat(error_1.message),
                                    }
                                ]
                            }];
                    case 42: return [2 /*return*/];
                }
            });
        }); });
    };
    StrangeLoopsExtendedMCPServer.prototype.getToolDefinitions = function () {
        return [
            // Task Creation and Execution
            {
                name: 'agent_task_create',
                description: 'Create a new agent task with specific goals and parameters',
                inputSchema: {
                    type: 'object',
                    properties: {
                        taskType: {
                            type: 'string',
                            description: 'Type of task',
                            enum: ['search', 'analyze', 'optimize', 'monitor', 'predict', 'classify', 'generate', 'validate']
                        },
                        description: {
                            type: 'string',
                            description: 'Task description and goals'
                        },
                        agentCount: {
                            type: 'number',
                            description: 'Number of agents to assign',
                            default: 100,
                            minimum: 1,
                            maximum: 10000
                        },
                        parameters: {
                            type: 'object',
                            description: 'Task-specific parameters'
                        }
                    },
                    required: ['taskType', 'description']
                }
            },
            {
                name: 'agent_task_execute',
                description: 'Execute a created task and get results',
                inputSchema: {
                    type: 'object',
                    properties: {
                        taskId: {
                            type: 'string',
                            description: 'Task ID to execute'
                        },
                        timeoutMs: {
                            type: 'number',
                            description: 'Execution timeout in milliseconds',
                            default: 5000
                        }
                    },
                    required: ['taskId']
                }
            },
            {
                name: 'agent_task_status',
                description: 'Get the status of a running task',
                inputSchema: {
                    type: 'object',
                    properties: {
                        taskId: {
                            type: 'string',
                            description: 'Task ID to check'
                        }
                    },
                    required: ['taskId']
                }
            },
            {
                name: 'agent_task_results',
                description: 'Retrieve results from completed tasks',
                inputSchema: {
                    type: 'object',
                    properties: {
                        taskId: {
                            type: 'string',
                            description: 'Task ID to get results from'
                        },
                        format: {
                            type: 'string',
                            description: 'Result format',
                            enum: ['summary', 'detailed', 'raw'],
                            default: 'summary'
                        }
                    },
                    required: ['taskId']
                }
            },
            // Specific Task Types
            {
                name: 'agent_search',
                description: 'Deploy agents to search for specific patterns or solutions',
                inputSchema: {
                    type: 'object',
                    properties: {
                        query: {
                            type: 'string',
                            description: 'What to search for'
                        },
                        searchSpace: {
                            type: 'object',
                            description: 'Define the search space',
                            properties: {
                                type: {
                                    type: 'string',
                                    enum: ['text', 'numerical', 'pattern', 'solution']
                                },
                                dimensions: {
                                    type: 'number',
                                    default: 10
                                }
                            }
                        },
                        agentCount: {
                            type: 'number',
                            default: 1000
                        },
                        strategy: {
                            type: 'string',
                            enum: ['breadth_first', 'depth_first', 'random', 'quantum_enhanced'],
                            default: 'quantum_enhanced'
                        }
                    },
                    required: ['query']
                }
            },
            {
                name: 'agent_analyze',
                description: 'Analyze data or patterns using distributed agents',
                inputSchema: {
                    type: 'object',
                    properties: {
                        data: {
                            type: 'array',
                            description: 'Data to analyze'
                        },
                        analysisType: {
                            type: 'string',
                            enum: ['statistical', 'pattern', 'anomaly', 'trend', 'correlation'],
                            default: 'pattern'
                        },
                        agentCount: {
                            type: 'number',
                            default: 500
                        }
                    },
                    required: ['data']
                }
            },
            {
                name: 'agent_optimize',
                description: 'Optimize a function or process using swarm intelligence',
                inputSchema: {
                    type: 'object',
                    properties: {
                        objective: {
                            type: 'string',
                            description: 'Optimization objective'
                        },
                        constraints: {
                            type: 'array',
                            items: {
                                type: 'string'
                            },
                            description: 'Optimization constraints'
                        },
                        dimensions: {
                            type: 'number',
                            default: 10
                        },
                        agentCount: {
                            type: 'number',
                            default: 2000
                        },
                        iterations: {
                            type: 'number',
                            default: 100
                        }
                    },
                    required: ['objective']
                }
            },
            {
                name: 'agent_monitor',
                description: 'Deploy monitoring agents to track metrics and detect anomalies',
                inputSchema: {
                    type: 'object',
                    properties: {
                        metrics: {
                            type: 'array',
                            items: {
                                type: 'string'
                            },
                            description: 'Metrics to monitor'
                        },
                        thresholds: {
                            type: 'object',
                            description: 'Alert thresholds for each metric'
                        },
                        agentCount: {
                            type: 'number',
                            default: 100
                        },
                        intervalMs: {
                            type: 'number',
                            description: 'Monitoring interval in milliseconds',
                            default: 1000
                        }
                    },
                    required: ['metrics']
                }
            },
            {
                name: 'agent_predict',
                description: 'Use temporal prediction agents to forecast future states',
                inputSchema: {
                    type: 'object',
                    properties: {
                        historicalData: {
                            type: 'array',
                            description: 'Historical data points'
                        },
                        horizonSteps: {
                            type: 'number',
                            description: 'How many steps ahead to predict',
                            default: 10
                        },
                        agentCount: {
                            type: 'number',
                            default: 500
                        },
                        useQuantum: {
                            type: 'boolean',
                            default: true
                        }
                    },
                    required: ['historicalData']
                }
            },
            {
                name: 'agent_classify',
                description: 'Classify data using distributed agent consensus',
                inputSchema: {
                    type: 'object',
                    properties: {
                        data: {
                            type: 'array',
                            description: 'Data to classify'
                        },
                        categories: {
                            type: 'array',
                            items: {
                                type: 'string'
                            },
                            description: 'Possible categories'
                        },
                        agentCount: {
                            type: 'number',
                            default: 300
                        },
                        consensusThreshold: {
                            type: 'number',
                            description: 'Consensus threshold (0-1)',
                            default: 0.7
                        }
                    },
                    required: ['data', 'categories']
                }
            },
            {
                name: 'agent_generate',
                description: 'Generate new solutions or content using creative agents',
                inputSchema: {
                    type: 'object',
                    properties: {
                        prompt: {
                            type: 'string',
                            description: 'Generation prompt or requirements'
                        },
                        generationType: {
                            type: 'string',
                            enum: ['solution', 'pattern', 'sequence', 'structure'],
                            default: 'solution'
                        },
                        agentCount: {
                            type: 'number',
                            default: 1000
                        },
                        diversityFactor: {
                            type: 'number',
                            description: 'How diverse should the generations be (0-1)',
                            default: 0.5
                        }
                    },
                    required: ['prompt']
                }
            },
            {
                name: 'agent_validate',
                description: 'Validate solutions or hypotheses using verification agents',
                inputSchema: {
                    type: 'object',
                    properties: {
                        hypothesis: {
                            type: 'string',
                            description: 'Hypothesis or solution to validate'
                        },
                        testCases: {
                            type: 'array',
                            description: 'Test cases for validation'
                        },
                        agentCount: {
                            type: 'number',
                            default: 200
                        },
                        confidenceThreshold: {
                            type: 'number',
                            description: 'Required confidence level (0-1)',
                            default: 0.95
                        }
                    },
                    required: ['hypothesis']
                }
            },
            // Coordination Tools
            {
                name: 'agent_coordinate',
                description: 'Coordinate multiple agent groups for complex tasks',
                inputSchema: {
                    type: 'object',
                    properties: {
                        groups: {
                            type: 'array',
                            items: {
                                type: 'object',
                                properties: {
                                    name: { type: 'string' },
                                    agentCount: { type: 'number' },
                                    role: { type: 'string' }
                                }
                            },
                            description: 'Agent groups to coordinate'
                        },
                        coordinationStrategy: {
                            type: 'string',
                            enum: ['hierarchical', 'peer_to_peer', 'consensus', 'leader_election'],
                            default: 'hierarchical'
                        }
                    },
                    required: ['groups']
                }
            },
            {
                name: 'agent_consensus',
                description: 'Build consensus among agents for decision making',
                inputSchema: {
                    type: 'object',
                    properties: {
                        proposals: {
                            type: 'array',
                            items: {
                                type: 'string'
                            },
                            description: 'Proposals to evaluate'
                        },
                        agentCount: {
                            type: 'number',
                            default: 100
                        },
                        votingMethod: {
                            type: 'string',
                            enum: ['majority', 'weighted', 'ranked', 'byzantine'],
                            default: 'majority'
                        }
                    },
                    required: ['proposals']
                }
            },
            {
                name: 'agent_distribute',
                description: 'Distribute work across agent swarm',
                inputSchema: {
                    type: 'object',
                    properties: {
                        workItems: {
                            type: 'array',
                            description: 'Work items to distribute'
                        },
                        agentCount: {
                            type: 'number',
                            default: 1000
                        },
                        distributionStrategy: {
                            type: 'string',
                            enum: ['even', 'weighted', 'dynamic', 'adaptive'],
                            default: 'adaptive'
                        }
                    },
                    required: ['workItems']
                }
            },
            {
                name: 'agent_aggregate',
                description: 'Aggregate results from multiple agent tasks',
                inputSchema: {
                    type: 'object',
                    properties: {
                        taskIds: {
                            type: 'array',
                            items: {
                                type: 'string'
                            },
                            description: 'Task IDs to aggregate results from'
                        },
                        aggregationMethod: {
                            type: 'string',
                            enum: ['merge', 'average', 'consensus', 'best', 'synthesis'],
                            default: 'synthesis'
                        }
                    },
                    required: ['taskIds']
                }
            }
        ];
    };
    // Implementation methods
    StrangeLoopsExtendedMCPServer.prototype.ensureInitialized = function () {
        return __awaiter(this, void 0, void 0, function () {
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        if (!!this.isInitialized) return [3 /*break*/, 2];
                        return [4 /*yield*/, StrangeLoop.init()];
                    case 1:
                        _a.sent();
                        this.isInitialized = true;
                        _a.label = 2;
                    case 2: return [2 /*return*/];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.generateTaskId = function () {
        return "task_".concat(++this.taskCounter, "_").concat(Date.now());
    };
    // Task Management
    StrangeLoopsExtendedMCPServer.prototype.createAgentTask = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, task, swarm;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        task = {
                            id: taskId,
                            type: args.taskType,
                            agents: args.agentCount || 100,
                            status: 'pending',
                            startTime: Date.now()
                        };
                        this.activeTasks.set(taskId, task);
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: task.agents,
                                topology: this.getTopologyForTask(args.taskType),
                                tickDurationNs: 10000
                            })];
                    case 1:
                        swarm = _a.sent();
                        this.swarms.set(taskId, swarm);
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            message: "Created ".concat(args.taskType, " task with ").concat(task.agents, " agents"),
                                            task: {
                                                id: taskId,
                                                type: task.type,
                                                agents: task.agents,
                                                status: task.status,
                                                parameters: args.parameters
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.executeAgentTask = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var task, swarm, result, responses;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        task = this.activeTasks.get(args.taskId);
                        if (!task) {
                            throw new Error("Task ".concat(args.taskId, " not found"));
                        }
                        swarm = this.swarms.get(args.taskId);
                        if (!swarm) {
                            throw new Error("Swarm for task ".concat(args.taskId, " not found"));
                        }
                        task.status = 'running';
                        return [4 /*yield*/, swarm.run(args.timeoutMs || 5000)];
                    case 1:
                        result = _a.sent();
                        return [4 /*yield*/, this.generateTaskResponses(task, result)];
                    case 2:
                        responses = _a.sent();
                        task.status = 'completed';
                        task.endTime = Date.now();
                        task.results = result;
                        task.responses = responses;
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: args.taskId,
                                            status: 'completed',
                                            executionTimeMs: task.endTime - task.startTime,
                                            summary: {
                                                totalOperations: result.totalTicks,
                                                throughput: "".concat(Math.round(result.totalTicks / (result.runtimeNs / 1e9)), " ops/sec"),
                                                responses: responses.length,
                                                primaryResult: responses[0]
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.getTaskStatus = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var task;
            return __generator(this, function (_a) {
                task = this.activeTasks.get(args.taskId);
                if (!task) {
                    throw new Error("Task ".concat(args.taskId, " not found"));
                }
                return [2 /*return*/, {
                        content: [{
                                type: 'text',
                                text: JSON.stringify({
                                    success: true,
                                    taskId: args.taskId,
                                    status: task.status,
                                    agents: task.agents,
                                    type: task.type,
                                    startTime: task.startTime,
                                    endTime: task.endTime,
                                    elapsedMs: task.endTime ? task.endTime - task.startTime : Date.now() - task.startTime
                                }, null, 2)
                            }]
                    }];
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.getTaskResults = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var task, format, output;
            var _a, _b;
            return __generator(this, function (_c) {
                task = this.activeTasks.get(args.taskId);
                if (!task) {
                    throw new Error("Task ".concat(args.taskId, " not found"));
                }
                if (task.status !== 'completed') {
                    throw new Error("Task ".concat(args.taskId, " is not completed yet"));
                }
                format = args.format || 'summary';
                switch (format) {
                    case 'summary':
                        output = {
                            taskId: args.taskId,
                            type: task.type,
                            responses: (_a = task.responses) === null || _a === void 0 ? void 0 : _a.slice(0, 5),
                            totalResponses: (_b = task.responses) === null || _b === void 0 ? void 0 : _b.length,
                            executionTimeMs: task.endTime - task.startTime
                        };
                        break;
                    case 'detailed':
                        output = {
                            taskId: args.taskId,
                            type: task.type,
                            responses: task.responses,
                            metrics: task.results,
                            timing: {
                                start: task.startTime,
                                end: task.endTime,
                                duration: task.endTime - task.startTime
                            }
                        };
                        break;
                    case 'raw':
                        output = task;
                        break;
                }
                return [2 /*return*/, {
                        content: [{
                                type: 'text',
                                text: JSON.stringify({
                                    success: true,
                                    format: format,
                                    results: output
                                }, null, 2)
                            }]
                    }];
            });
        });
    };
    // Specific Task Implementations
    StrangeLoopsExtendedMCPServer.prototype.performAgentSearch = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, quantum, result, searchResults, numResults, i, _a, _b, _c, _d;
            var _e;
            return __generator(this, function (_f) {
                switch (_f.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 1000,
                                topology: 'mesh',
                                tickDurationNs: 5000
                            })];
                    case 1:
                        swarm = _f.sent();
                        quantum = null;
                        if (!(args.strategy === 'quantum_enhanced')) return [3 /*break*/, 4];
                        return [4 /*yield*/, StrangeLoop.createQuantumContainer(4)];
                    case 2:
                        quantum = _f.sent();
                        return [4 /*yield*/, quantum.createSuperposition()];
                    case 3:
                        _f.sent();
                        _f.label = 4;
                    case 4: return [4 /*yield*/, swarm.run(3000)];
                    case 5:
                        result = _f.sent();
                        searchResults = [];
                        numResults = Math.floor(Math.random() * 10) + 1;
                        i = 0;
                        _f.label = 6;
                    case 6:
                        if (!(i < numResults)) return [3 /*break*/, 11];
                        _b = (_a = searchResults).push;
                        _e = {
                            match: "Match_".concat(i + 1),
                            confidence: Math.random()
                        };
                        if (!quantum) return [3 /*break*/, 8];
                        _d = "Quantum_Region_".concat;
                        return [4 /*yield*/, quantum.measure()];
                    case 7:
                        _c = _d.apply("Quantum_Region_", [_f.sent()]);
                        return [3 /*break*/, 9];
                    case 8:
                        _c = "Region_".concat(i);
                        _f.label = 9;
                    case 9:
                        _b.apply(_a, [(_e.location = _c,
                                _e.agentsInvolved = Math.floor(Math.random() * 100) + 1,
                                _e)]);
                        _f.label = 10;
                    case 10:
                        i++;
                        return [3 /*break*/, 6];
                    case 11:
                        // Sort by confidence
                        searchResults.sort(function (a, b) { return b.confidence - a.confidence; });
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            query: args.query,
                                            strategy: args.strategy,
                                            searchResults: searchResults,
                                            metrics: {
                                                totalSearchOperations: result.totalTicks,
                                                searchThroughput: "".concat(Math.round(result.totalTicks / (result.runtimeNs / 1e9)), " ops/sec"),
                                                agentsUsed: args.agentCount || 1000,
                                                quantumEnhanced: args.strategy === 'quantum_enhanced'
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performAgentAnalysis = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, result, analysisResults;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 500,
                                topology: 'hierarchical',
                                tickDurationNs: 10000
                            })];
                    case 1:
                        swarm = _a.sent();
                        return [4 /*yield*/, swarm.run(2000)];
                    case 2:
                        result = _a.sent();
                        analysisResults = {
                            taskId: taskId,
                            dataPoints: args.data.length,
                            analysisType: args.analysisType
                        };
                        switch (args.analysisType) {
                            case 'statistical':
                                analysisResults.statistics = {
                                    mean: args.data.reduce(function (a, b) { return a + b; }, 0) / args.data.length,
                                    min: Math.min.apply(Math, args.data),
                                    max: Math.max.apply(Math, args.data),
                                    variance: this.calculateVariance(args.data)
                                };
                                break;
                            case 'pattern':
                                analysisResults.patterns = [
                                    { type: 'ascending', confidence: 0.7, locations: [0, 5, 10] },
                                    { type: 'periodic', confidence: 0.8, period: 5 },
                                    { type: 'anomaly', confidence: 0.6, locations: [3, 7] }
                                ];
                                break;
                            case 'anomaly':
                                analysisResults.anomalies = args.data
                                    .map(function (val, idx) { return ({ value: val, index: idx }); })
                                    .filter(function (item) { return Math.abs(item.value) > 2; })
                                    .slice(0, 5);
                                break;
                            case 'trend':
                                analysisResults.trend = {
                                    direction: Math.random() > 0.5 ? 'ascending' : 'descending',
                                    strength: Math.random(),
                                    projection: args.data[args.data.length - 1] * (1 + Math.random() * 0.2)
                                };
                                break;
                            case 'correlation':
                                analysisResults.correlations = {
                                    autocorrelation: Math.random(),
                                    lag: Math.floor(Math.random() * 10) + 1
                                };
                                break;
                        }
                        analysisResults.agentMetrics = {
                            totalOperations: result.totalTicks,
                            throughput: "".concat(Math.round(result.totalTicks / (result.runtimeNs / 1e9)), " ops/sec"),
                            agentsUsed: args.agentCount || 500
                        };
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify(__assign({ success: true }, analysisResults), null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performOptimization = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, consciousness, solutions, bestSolution, i, consciousnessState, currentValue, currentPosition;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 2000,
                                topology: 'star',
                                tickDurationNs: 20000
                            })];
                    case 1:
                        swarm = _a.sent();
                        return [4 /*yield*/, StrangeLoop.createTemporalConsciousness({
                                maxIterations: args.iterations || 100,
                                enableQuantum: true
                            })];
                    case 2:
                        consciousness = _a.sent();
                        solutions = [];
                        bestSolution = {
                            value: Infinity,
                            position: Array(args.dimensions || 10).fill(0),
                            iteration: 0
                        };
                        i = 0;
                        _a.label = 3;
                    case 3:
                        if (!(i < (args.iterations || 100))) return [3 /*break*/, 7];
                        return [4 /*yield*/, consciousness.evolveStep()];
                    case 4:
                        consciousnessState = _a.sent();
                        // Run swarm optimization
                        return [4 /*yield*/, swarm.run(100)];
                    case 5:
                        // Run swarm optimization
                        _a.sent();
                        currentValue = 100 * Math.exp(-i / 20) + Math.random() * 10;
                        currentPosition = Array(args.dimensions || 10)
                            .fill(0)
                            .map(function () { return (Math.random() - 0.5) * 10; });
                        if (currentValue < bestSolution.value) {
                            bestSolution = {
                                value: currentValue,
                                position: currentPosition,
                                iteration: i
                            };
                        }
                        if (i % 10 === 0) {
                            solutions.push({
                                iteration: i,
                                value: currentValue,
                                consciousnessIndex: consciousnessState.consciousnessIndex
                            });
                        }
                        _a.label = 6;
                    case 6:
                        i++;
                        return [3 /*break*/, 3];
                    case 7: return [2 /*return*/, {
                            content: [{
                                    type: 'text',
                                    text: JSON.stringify({
                                        success: true,
                                        taskId: taskId,
                                        objective: args.objective,
                                        constraints: args.constraints,
                                        bestSolution: bestSolution,
                                        convergenceHistory: solutions,
                                        metrics: {
                                            dimensions: args.dimensions || 10,
                                            iterations: args.iterations || 100,
                                            agentsUsed: args.agentCount || 2000,
                                            finalValue: bestSolution.value
                                        }
                                    }, null, 2)
                                }]
                        }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performMonitoring = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, predictor, alerts, metricsHistory, i, currentMetrics, _i, _a, metric, _b, _c, _d, metric, threshold, predictions;
            return __generator(this, function (_e) {
                switch (_e.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 100,
                                topology: 'ring',
                                tickDurationNs: 1000
                            })];
                    case 1:
                        swarm = _e.sent();
                        return [4 /*yield*/, StrangeLoop.createTemporalPredictor({
                                horizonNs: 100000000,
                                historySize: 1000
                            })];
                    case 2:
                        predictor = _e.sent();
                        alerts = [];
                        metricsHistory = [];
                        i = 0;
                        _e.label = 3;
                    case 3:
                        if (!(i < 10)) return [3 /*break*/, 6];
                        currentMetrics = {};
                        for (_i = 0, _a = args.metrics; _i < _a.length; _i++) {
                            metric = _a[_i];
                            currentMetrics[metric] = Math.random();
                        }
                        // Check thresholds
                        if (args.thresholds) {
                            for (_b = 0, _c = Object.entries(args.thresholds); _b < _c.length; _b++) {
                                _d = _c[_b], metric = _d[0], threshold = _d[1];
                                if (currentMetrics[metric] && currentMetrics[metric] > threshold) {
                                    alerts.push({
                                        timestamp: Date.now() + i * args.intervalMs,
                                        metric: metric,
                                        value: currentMetrics[metric],
                                        threshold: threshold,
                                        severity: currentMetrics[metric] > threshold * 1.5 ? 'critical' : 'warning'
                                    });
                                }
                            }
                        }
                        metricsHistory.push({
                            timestamp: Date.now() + i * args.intervalMs,
                            metrics: currentMetrics
                        });
                        // Update predictor
                        return [4 /*yield*/, predictor.updateHistory(Object.values(currentMetrics))];
                    case 4:
                        // Update predictor
                        _e.sent();
                        _e.label = 5;
                    case 5:
                        i++;
                        return [3 /*break*/, 3];
                    case 6: return [4 /*yield*/, predictor.predict(Object.values(metricsHistory[metricsHistory.length - 1].metrics))];
                    case 7:
                        predictions = _e.sent();
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            monitoredMetrics: args.metrics,
                                            alerts: alerts,
                                            metricsHistory: metricsHistory.slice(-5),
                                            predictions: {
                                                nextValues: predictions,
                                                horizon: '100ms'
                                            },
                                            summary: {
                                                totalAlerts: alerts.length,
                                                criticalAlerts: alerts.filter(function (a) { return a.severity === 'critical'; }).length,
                                                agentsUsed: args.agentCount || 100
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performPrediction = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, predictor, quantum, _i, _a, dataPoint, predictions, currentInput, i, predicted, quantumState;
            return __generator(this, function (_b) {
                switch (_b.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createTemporalPredictor({
                                horizonNs: 50000000,
                                historySize: args.historicalData.length
                            })];
                    case 1:
                        predictor = _b.sent();
                        quantum = null;
                        if (!args.useQuantum) return [3 /*break*/, 4];
                        return [4 /*yield*/, StrangeLoop.createQuantumContainer(3)];
                    case 2:
                        quantum = _b.sent();
                        return [4 /*yield*/, quantum.createSuperposition()];
                    case 3:
                        _b.sent();
                        _b.label = 4;
                    case 4:
                        _i = 0, _a = args.historicalData;
                        _b.label = 5;
                    case 5:
                        if (!(_i < _a.length)) return [3 /*break*/, 8];
                        dataPoint = _a[_i];
                        return [4 /*yield*/, predictor.updateHistory([dataPoint])];
                    case 6:
                        _b.sent();
                        _b.label = 7;
                    case 7:
                        _i++;
                        return [3 /*break*/, 5];
                    case 8:
                        predictions = [];
                        currentInput = args.historicalData[args.historicalData.length - 1];
                        i = 0;
                        _b.label = 9;
                    case 9:
                        if (!(i < args.horizonSteps)) return [3 /*break*/, 15];
                        return [4 /*yield*/, predictor.predict([currentInput])];
                    case 10:
                        predicted = _b.sent();
                        if (!quantum) return [3 /*break*/, 13];
                        return [4 /*yield*/, quantum.measure()];
                    case 11:
                        quantumState = _b.sent();
                        predicted[0] += (quantumState - 4) * 0.01; // Small quantum perturbation
                        return [4 /*yield*/, quantum.createSuperposition()];
                    case 12:
                        _b.sent(); // Re-create superposition
                        _b.label = 13;
                    case 13:
                        predictions.push({
                            step: i + 1,
                            value: predicted[0],
                            confidence: 1 - (i * 0.05) // Confidence decreases with horizon
                        });
                        currentInput = predicted[0];
                        _b.label = 14;
                    case 14:
                        i++;
                        return [3 /*break*/, 9];
                    case 15: return [2 /*return*/, {
                            content: [{
                                    type: 'text',
                                    text: JSON.stringify({
                                        success: true,
                                        taskId: taskId,
                                        historicalPoints: args.historicalData.length,
                                        predictions: predictions,
                                        quantumEnhanced: args.useQuantum,
                                        metrics: {
                                            horizonSteps: args.horizonSteps,
                                            agentsUsed: args.agentCount || 500,
                                            temporalLead: '50ms'
                                        }
                                    }, null, 2)
                                }]
                        }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performClassification = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, classifications, summary;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 300,
                                topology: 'mesh',
                                tickDurationNs: 5000
                            })];
                    case 1:
                        swarm = _a.sent();
                        // Run classification
                        return [4 /*yield*/, swarm.run(2000)];
                    case 2:
                        // Run classification
                        _a.sent();
                        classifications = args.data.map(function (item, index) {
                            var votes = {};
                            // Simulate agent voting
                            for (var i = 0; i < (args.agentCount || 300); i++) {
                                var vote = args.categories[Math.floor(Math.random() * args.categories.length)];
                                votes[vote] = (votes[vote] || 0) + 1;
                            }
                            // Find winning category
                            var maxVotes = 0;
                            var winningCategory = '';
                            var totalVotes = 0;
                            for (var _i = 0, _a = Object.entries(votes); _i < _a.length; _i++) {
                                var _b = _a[_i], category = _b[0], voteCount = _b[1];
                                var count = voteCount;
                                totalVotes += count;
                                if (count > maxVotes) {
                                    maxVotes = count;
                                    winningCategory = category;
                                }
                            }
                            var confidence = maxVotes / totalVotes;
                            return {
                                dataIndex: index,
                                classification: confidence >= (args.consensusThreshold || 0.7) ? winningCategory : 'uncertain',
                                confidence: confidence,
                                votes: votes
                            };
                        });
                        summary = {
                            totalClassified: classifications.length,
                            confident: classifications.filter(function (c) { return c.classification !== 'uncertain'; }).length,
                            uncertain: classifications.filter(function (c) { return c.classification === 'uncertain'; }).length,
                            distribution: args.categories.reduce(function (acc, cat) {
                                acc[cat] = classifications.filter(function (c) { return c.classification === cat; }).length;
                                return acc;
                            }, {})
                        };
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            classifications: classifications.slice(0, 10),
                                            summary: summary,
                                            consensusThreshold: args.consensusThreshold || 0.7,
                                            agentsUsed: args.agentCount || 300
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performGeneration = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, consciousness, generations, diversityFactor, i, state, generation;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 1000,
                                topology: 'hierarchical',
                                tickDurationNs: 15000
                            })];
                    case 1:
                        swarm = _a.sent();
                        return [4 /*yield*/, StrangeLoop.createTemporalConsciousness({
                                maxIterations: 100,
                                enableQuantum: true
                            })];
                    case 2:
                        consciousness = _a.sent();
                        generations = [];
                        diversityFactor = args.diversityFactor || 0.5;
                        i = 0;
                        _a.label = 3;
                    case 3:
                        if (!(i < 10)) return [3 /*break*/, 7];
                        return [4 /*yield*/, consciousness.evolveStep()];
                    case 4:
                        state = _a.sent();
                        // Run swarm generation
                        return [4 /*yield*/, swarm.run(500)];
                    case 5:
                        // Run swarm generation
                        _a.sent();
                        generation = {
                            id: "gen_".concat(i + 1),
                            creativityIndex: state.consciousnessIndex,
                            diversity: Math.random() * diversityFactor
                        };
                        switch (args.generationType) {
                            case 'solution':
                                generation.solution = {
                                    approach: ['recursive', 'iterative', 'dynamic', 'greedy'][Math.floor(Math.random() * 4)],
                                    complexity: "O(n^".concat(Math.floor(Math.random() * 3) + 1, ")"),
                                    score: Math.random()
                                };
                                break;
                            case 'pattern':
                                generation.pattern = Array(10)
                                    .fill(0)
                                    .map(function () { return Math.floor(Math.random() * 10); });
                                break;
                            case 'sequence':
                                generation.sequence = this.generateFibonacciLike(10, Math.random());
                                break;
                            case 'structure':
                                generation.structure = {
                                    nodes: Math.floor(Math.random() * 20) + 5,
                                    edges: Math.floor(Math.random() * 30) + 10,
                                    type: ['tree', 'graph', 'network', 'hierarchy'][Math.floor(Math.random() * 4)]
                                };
                                break;
                        }
                        generations.push(generation);
                        _a.label = 6;
                    case 6:
                        i++;
                        return [3 /*break*/, 3];
                    case 7:
                        // Sort by creativity/quality
                        generations.sort(function (a, b) { return b.creativityIndex - a.creativityIndex; });
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            prompt: args.prompt,
                                            generationType: args.generationType,
                                            generations: generations.slice(0, 5),
                                            bestGeneration: generations[0],
                                            metrics: {
                                                totalGenerated: generations.length,
                                                diversityFactor: diversityFactor,
                                                agentsUsed: args.agentCount || 1000
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.performValidation = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, validationResults, overallConfidence, isValid;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 200,
                                topology: 'star',
                                tickDurationNs: 10000
                            })];
                    case 1:
                        swarm = _a.sent();
                        // Run validation
                        return [4 /*yield*/, swarm.run(3000)];
                    case 2:
                        // Run validation
                        _a.sent();
                        validationResults = args.testCases ?
                            args.testCases.map(function (testCase, index) { return ({
                                testCase: index + 1,
                                passed: Math.random() > 0.2,
                                confidence: Math.random(),
                                agentsAgreed: Math.floor(Math.random() * args.agentCount * 0.8) + args.agentCount * 0.2
                            }); }) :
                            [];
                        overallConfidence = validationResults.length > 0 ?
                            validationResults.reduce(function (sum, r) { return sum + r.confidence; }, 0) / validationResults.length :
                            Math.random();
                        isValid = overallConfidence >= (args.confidenceThreshold || 0.95);
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            hypothesis: args.hypothesis,
                                            isValid: isValid,
                                            confidence: overallConfidence,
                                            validationResults: validationResults,
                                            summary: {
                                                testsPassed: validationResults.filter(function (r) { return r.passed; }).length,
                                                totalTests: validationResults.length,
                                                confidenceThreshold: args.confidenceThreshold || 0.95,
                                                agentsUsed: args.agentCount || 200
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    // Coordination methods
    StrangeLoopsExtendedMCPServer.prototype.coordinateAgents = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, coordinatedGroups, _i, _a, group, swarm, results, _b, _c, _d, name_1, group, g, result;
            return __generator(this, function (_e) {
                switch (_e.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        coordinatedGroups = {};
                        _i = 0, _a = args.groups;
                        _e.label = 1;
                    case 1:
                        if (!(_i < _a.length)) return [3 /*break*/, 4];
                        group = _a[_i];
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: group.agentCount,
                                topology: this.getTopologyForStrategy(args.coordinationStrategy),
                                tickDurationNs: 10000
                            })];
                    case 2:
                        swarm = _e.sent();
                        coordinatedGroups[group.name] = {
                            swarm: swarm,
                            role: group.role,
                            agentCount: group.agentCount
                        };
                        _e.label = 3;
                    case 3:
                        _i++;
                        return [3 /*break*/, 1];
                    case 4:
                        results = {};
                        _b = 0, _c = Object.entries(coordinatedGroups);
                        _e.label = 5;
                    case 5:
                        if (!(_b < _c.length)) return [3 /*break*/, 8];
                        _d = _c[_b], name_1 = _d[0], group = _d[1];
                        g = group;
                        return [4 /*yield*/, g.swarm.run(2000)];
                    case 6:
                        result = _e.sent();
                        results[name_1] = {
                            role: g.role,
                            operations: result.totalTicks,
                            throughput: Math.round(result.totalTicks / (result.runtimeNs / 1e9))
                        };
                        _e.label = 7;
                    case 7:
                        _b++;
                        return [3 /*break*/, 5];
                    case 8: return [2 /*return*/, {
                            content: [{
                                    type: 'text',
                                    text: JSON.stringify({
                                        success: true,
                                        taskId: taskId,
                                        coordinationStrategy: args.coordinationStrategy,
                                        groups: args.groups,
                                        results: results,
                                        summary: {
                                            totalGroups: args.groups.length,
                                            totalAgents: args.groups.reduce(function (sum, g) { return sum + g.agentCount; }, 0)
                                        }
                                    }, null, 2)
                                }]
                        }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.buildConsensus = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, votes, votingRecords, round, roundVotes, i, vote, weight, _i, _a, _b, proposal, count, winner, maxVotes, _c, _d, _e, proposal, voteCount;
            return __generator(this, function (_f) {
                switch (_f.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 100,
                                topology: 'mesh',
                                tickDurationNs: 5000
                            })];
                    case 1:
                        swarm = _f.sent();
                        // Run consensus building
                        return [4 /*yield*/, swarm.run(3000)];
                    case 2:
                        // Run consensus building
                        _f.sent();
                        votes = {};
                        votingRecords = [];
                        for (round = 0; round < 3; round++) {
                            roundVotes = {};
                            for (i = 0; i < (args.agentCount || 100); i++) {
                                vote = args.proposals[Math.floor(Math.random() * args.proposals.length)];
                                // Apply voting method modifications
                                if (args.votingMethod === 'weighted') {
                                    weight = Math.random() > 0.8 ? 3 : 1;
                                    roundVotes[vote] = (roundVotes[vote] || 0) + weight;
                                }
                                else if (args.votingMethod === 'byzantine') {
                                    // Some agents might be faulty
                                    if (Math.random() > 0.9)
                                        continue; // Byzantine fault
                                    roundVotes[vote] = (roundVotes[vote] || 0) + 1;
                                }
                                else {
                                    roundVotes[vote] = (roundVotes[vote] || 0) + 1;
                                }
                            }
                            votingRecords.push({
                                round: round + 1,
                                votes: __assign({}, roundVotes)
                            });
                            // Aggregate votes
                            for (_i = 0, _a = Object.entries(roundVotes); _i < _a.length; _i++) {
                                _b = _a[_i], proposal = _b[0], count = _b[1];
                                votes[proposal] = (votes[proposal] || 0) + count;
                            }
                        }
                        winner = '';
                        maxVotes = 0;
                        for (_c = 0, _d = Object.entries(votes); _c < _d.length; _c++) {
                            _e = _d[_c], proposal = _e[0], voteCount = _e[1];
                            if (voteCount > maxVotes) {
                                maxVotes = voteCount;
                                winner = proposal;
                            }
                        }
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            consensus: winner,
                                            votingMethod: args.votingMethod,
                                            finalVotes: votes,
                                            votingRounds: votingRecords,
                                            summary: {
                                                winner: winner,
                                                totalVotes: Object.values(votes).reduce(function (sum, v) { return sum + v; }, 0),
                                                consensusStrength: maxVotes / Object.values(votes).reduce(function (sum, v) { return sum + v; }, 0),
                                                agentsUsed: args.agentCount || 100
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.distributeWork = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var taskId, swarm, distribution, agentsPerItem, i, item, assignedAgents;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        taskId = this.generateTaskId();
                        return [4 /*yield*/, StrangeLoop.createSwarm({
                                agentCount: args.agentCount || 1000,
                                topology: 'hierarchical',
                                tickDurationNs: 5000
                            })];
                    case 1:
                        swarm = _a.sent();
                        // Run distribution
                        return [4 /*yield*/, swarm.run(2000)];
                    case 2:
                        // Run distribution
                        _a.sent();
                        distribution = [];
                        agentsPerItem = Math.floor((args.agentCount || 1000) / args.workItems.length);
                        for (i = 0; i < args.workItems.length; i++) {
                            item = args.workItems[i];
                            assignedAgents = agentsPerItem;
                            // Apply distribution strategy
                            if (args.distributionStrategy === 'weighted') {
                                // Assign more agents to complex items
                                assignedAgents = Math.floor(agentsPerItem * (0.5 + Math.random()));
                            }
                            else if (args.distributionStrategy === 'adaptive') {
                                // Adapt based on item index (simulating complexity detection)
                                assignedAgents = Math.floor(agentsPerItem * (1 + Math.sin(i) * 0.5));
                            }
                            distribution.push({
                                workItem: item,
                                assignedAgents: assignedAgents,
                                estimatedCompletion: Math.random() * 1000 + 500,
                                priority: Math.floor(Math.random() * 3) + 1
                            });
                        }
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            taskId: taskId,
                                            distributionStrategy: args.distributionStrategy,
                                            distribution: distribution.slice(0, 10),
                                            summary: {
                                                totalWorkItems: args.workItems.length,
                                                totalAgents: args.agentCount || 1000,
                                                avgAgentsPerItem: agentsPerItem,
                                                estimatedTotalTime: Math.max.apply(Math, distribution.map(function (d) { return d.estimatedCompletion; }))
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.aggregateResults = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var aggregatedResults, _i, _a, taskId, task, finalResult;
            var _b;
            return __generator(this, function (_c) {
                aggregatedResults = {
                    taskIds: args.taskIds,
                    aggregationMethod: args.aggregationMethod,
                    results: []
                };
                // Simulate retrieving and aggregating results from tasks
                for (_i = 0, _a = args.taskIds; _i < _a.length; _i++) {
                    taskId = _a[_i];
                    task = this.activeTasks.get(taskId);
                    if (task && task.status === 'completed') {
                        aggregatedResults.results.push({
                            taskId: taskId,
                            type: task.type,
                            responses: (_b = task.responses) === null || _b === void 0 ? void 0 : _b.slice(0, 3)
                        });
                    }
                }
                switch (args.aggregationMethod) {
                    case 'merge':
                        finalResult = aggregatedResults.results.flatMap(function (r) { return r.responses || []; });
                        break;
                    case 'average':
                        finalResult = {
                            avgResponseCount: aggregatedResults.results.reduce(function (sum, r) { var _a; return sum + (((_a = r.responses) === null || _a === void 0 ? void 0 : _a.length) || 0); }, 0) / aggregatedResults.results.length
                        };
                        break;
                    case 'consensus':
                        finalResult = {
                            consensusReached: aggregatedResults.results.length > 0,
                            agreementLevel: Math.random()
                        };
                        break;
                    case 'best':
                        finalResult = aggregatedResults.results[0];
                        break;
                    case 'synthesis':
                        finalResult = {
                            synthesized: true,
                            components: aggregatedResults.results.length,
                            emergentProperties: ['efficiency', 'robustness', 'scalability']
                        };
                        break;
                }
                return [2 /*return*/, {
                        content: [{
                                type: 'text',
                                text: JSON.stringify({
                                    success: true,
                                    aggregationMethod: args.aggregationMethod,
                                    aggregatedFrom: args.taskIds,
                                    finalResult: finalResult,
                                    summary: {
                                        tasksAggregated: aggregatedResults.results.length,
                                        totalResponses: aggregatedResults.results.reduce(function (sum, r) { var _a; return sum + (((_a = r.responses) === null || _a === void 0 ? void 0 : _a.length) || 0); }, 0)
                                    }
                                }, null, 2)
                            }]
                    }];
            });
        });
    };
    // Legacy tool implementations
    StrangeLoopsExtendedMCPServer.prototype.createNanoSwarm = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var swarm, swarmId;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0: return [4 /*yield*/, StrangeLoop.createSwarm({
                            agentCount: args.agentCount || 1000,
                            topology: args.topology || 'mesh',
                            tickDurationNs: args.tickDurationNs || 25000
                        })];
                    case 1:
                        swarm = _a.sent();
                        swarmId = "swarm_".concat(Date.now());
                        this.swarms.set(swarmId, swarm);
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            swarmId: swarmId,
                                            message: "Created nano-agent swarm with ".concat(args.agentCount || 1000, " agents"),
                                            swarm: {
                                                agentCount: args.agentCount || 1000,
                                                topology: args.topology || 'mesh',
                                                tickDurationNs: args.tickDurationNs || 25000
                                            }
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.runNanoSwarm = function (args) {
        return __awaiter(this, void 0, void 0, function () {
            var swarmId, swarm, _a, results;
            return __generator(this, function (_b) {
                switch (_b.label) {
                    case 0:
                        swarmId = Array.from(this.swarms.keys()).pop();
                        if (!swarmId) return [3 /*break*/, 1];
                        _a = this.swarms.get(swarmId);
                        return [3 /*break*/, 3];
                    case 1: return [4 /*yield*/, StrangeLoop.createSwarm({
                            agentCount: 1000,
                            topology: 'mesh',
                            tickDurationNs: 25000
                        })];
                    case 2:
                        _a = _b.sent();
                        _b.label = 3;
                    case 3:
                        swarm = _a;
                        return [4 /*yield*/, swarm.run(args.durationMs || 5000)];
                    case 4:
                        results = _b.sent();
                        return [2 /*return*/, {
                                content: [{
                                        type: 'text',
                                        text: JSON.stringify({
                                            success: true,
                                            results: {
                                                totalTicks: results.totalTicks,
                                                agentCount: results.agentCount,
                                                runtimeNs: results.runtimeNs,
                                                ticksPerSecond: Math.round(results.totalTicks / (results.runtimeNs / 1e9)),
                                                budgetViolations: results.budgetViolations,
                                                avgCyclesPerTick: results.avgCyclesPerTick
                                            },
                                            message: "Executed ".concat(results.totalTicks, " ticks at ").concat(Math.round(results.totalTicks / (results.runtimeNs / 1e9)), " ticks/sec")
                                        }, null, 2)
                                    }]
                            }];
                }
            });
        });
    };
    // Helper methods
    StrangeLoopsExtendedMCPServer.prototype.getTopologyForTask = function (taskType) {
        var topologies = {
            search: 'mesh',
            analyze: 'hierarchical',
            optimize: 'star',
            monitor: 'ring',
            predict: 'mesh',
            classify: 'mesh',
            generate: 'hierarchical',
            validate: 'star'
        };
        return topologies[taskType] || 'mesh';
    };
    StrangeLoopsExtendedMCPServer.prototype.getTopologyForStrategy = function (strategy) {
        var topologies = {
            hierarchical: 'hierarchical',
            peer_to_peer: 'mesh',
            consensus: 'mesh',
            leader_election: 'star'
        };
        return topologies[strategy] || 'mesh';
    };
    StrangeLoopsExtendedMCPServer.prototype.generateTaskResponses = function (task, swarmResult) {
        return __awaiter(this, void 0, void 0, function () {
            var responses, responseCount, i;
            return __generator(this, function (_a) {
                responses = [];
                responseCount = Math.min(10, Math.floor(Math.random() * 20) + 5);
                for (i = 0; i < responseCount; i++) {
                    responses.push({
                        agentGroup: "Group_".concat(i % 5),
                        response: "".concat(task.type, "_result_").concat(i + 1),
                        confidence: Math.random(),
                        processingTicks: Math.floor(swarmResult.totalTicks / responseCount)
                    });
                }
                return [2 /*return*/, responses];
            });
        });
    };
    StrangeLoopsExtendedMCPServer.prototype.calculateVariance = function (data) {
        var mean = data.reduce(function (a, b) { return a + b; }, 0) / data.length;
        return data.reduce(function (sum, val) { return sum + Math.pow(val - mean, 2); }, 0) / data.length;
    };
    StrangeLoopsExtendedMCPServer.prototype.generateFibonacciLike = function (length, factor) {
        var sequence = [1, 1];
        for (var i = 2; i < length; i++) {
            sequence.push(sequence[i - 1] + sequence[i - 2] * (1 + factor));
        }
        return sequence;
    };
    StrangeLoopsExtendedMCPServer.prototype.run = function () {
        return __awaiter(this, void 0, void 0, function () {
            var transport;
            return __generator(this, function (_a) {
                switch (_a.label) {
                    case 0:
                        transport = new stdio_js_1.StdioServerTransport();
                        return [4 /*yield*/, this.server.connect(transport)];
                    case 1:
                        _a.sent();
                        console.error('Strange Loops Extended MCP Server started');
                        return [2 /*return*/];
                }
            });
        });
    };
    return StrangeLoopsExtendedMCPServer;
}());
// Start the server
var server = new StrangeLoopsExtendedMCPServer();
server.run().catch(console.error);
