1846 lines
90 KiB
JavaScript
1846 lines
90 KiB
JavaScript
#!/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) {
|
|
for (var s, i = 1, n = arguments.length; i < n; i++) {
|
|
s = arguments[i];
|
|
for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p))
|
|
t[p] = s[p];
|
|
}
|
|
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) {
|
|
var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g = Object.create((typeof Iterator === "function" ? Iterator : Object).prototype);
|
|
return g.next = verb(0), g["throw"] = verb(1), g["return"] = verb(2), typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
|
|
function verb(n) { return function (v) { return step([n, v]); }; }
|
|
function step(op) {
|
|
if (f) throw new TypeError("Generator is already executing.");
|
|
while (g && (g = 0, op[0] && (_ = 0)), _) try {
|
|
if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
|
|
if (y = 0, t) op = [op[0] & 2, t.value];
|
|
switch (op[0]) {
|
|
case 0: case 1: t = op; break;
|
|
case 4: _.label++; return { value: op[1], done: false };
|
|
case 5: _.label++; y = op[1]; op = [0]; continue;
|
|
case 7: op = _.ops.pop(); _.trys.pop(); continue;
|
|
default:
|
|
if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
|
|
if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
|
|
if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
|
|
if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
|
|
if (t[2]) _.ops.pop();
|
|
_.trys.pop(); continue;
|
|
}
|
|
op = body.call(thisArg, _);
|
|
} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
|
|
if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
|
|
}
|
|
};
|
|
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);
|