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2025-04-03

Claude 3.7 Swarm avec cohérence de champ: un serveur de protocole de contexte de modèle (MCP) qui orchestre plusieurs instances de sonnet Claude 3.7 spécialisées dans un essaim inspiré quantique. Il crée un effet de cohérence sur le terrain à travers la reconnaissance des modèles, la théorie de l'information et les spécialistes du raisonnement pour produire des réponses optimalement cohérentes à partir de l'intelligence d'ensemble.

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MindMesh MCP Server

A Model Context Protocol (MCP) server implementation that creates a quantum-inspired swarm of Claude 3.7 Sonnet instances with field coherence optimization. This server enables enriched reasoning through multiple specialized LLM instances that work together with emergent properties.

Features

  • Quantum-Inspired Field Computing: Uses a field-based model to maintain coherence between Claude instances
  • WebContainer Integration: Full stack sandboxed environment for execution
  • PGLite with Vector Storage: Efficient vector database with pgvector extension
  • Multiple Claude Specializations: Instances focus on pattern recognition, information synthesis, and reasoning
  • Coherence Optimization: Selects the most coherent outputs across instances
  • Extended Thinking Support: Optional 128k token thinking capability
  • Live Query Updates: Real-time coherence notifications through PGLite live extension
  • VoyageAI Embeddings: High-quality embeddings using VoyageAI's state-of-the-art models (voyage-3-large)

Prerequisites

  • Node.js 18.x or higher
  • Anthropic API key with access to Claude 3.7 Sonnet
  • VoyageAI API key (optional but recommended for better embeddings)

Installation

  1. Clone this repository:

    git clone https://github.com/wheattoast11/mcp-mindmesh.git
    cd mcp-mindmesh
    
  2. Install dependencies:

    npm install
    
  3. Create a .env file by copying the template:

    cp .env.template .env
    
  4. Edit .env and add your Anthropic API key, VoyageAI API key (optional), and adjust other settings as needed.

Usage

Starting the Server

Build and start the server:

npm run build
npm start

For development with auto-reload:

npm run dev

Connecting to the Server

You can connect to this MCP server using any MCP client, such as:

  1. Claude Desktop Application for Windows (official Anthropic client)
  2. Cursor IDE's agent capabilities
  3. Cline VSCode extension
  4. Any other MCP-compatible client

The server will be available at http://localhost:3000 by default (or whichever port you specified in the .env file).

Using the Reasoning Tool

The main tool provided by this server is reason_with_swarm. This tool takes a prompt and processes it through multiple specialized Claude instances, returning the most coherent result.

Example usage in Claude Desktop:

Please use the swarm to analyze the relationship between quantum field theory and consciousness.

Configuration Options

All configuration options can be set in the .env file:

Environment Variable Description Default
ANTHROPIC_API_KEY Your Anthropic API key (required)
VOYAGE_API_KEY Your VoyageAI API key (optional)
PORT HTTP server port 3000
STDIO_TRANSPORT Use stdio transport instead of HTTP false
CLAUDE_INSTANCES Number of Claude instances in the swarm 8
USE_EXTENDED_THINKING Enable 128k extended thinking true
COHERENCE_THRESHOLD Minimum coherence threshold 0.7
EMBEDDING_MODEL VoyageAI embedding model to use voyage-3-large
DB_PATH Path for the PGLite database "idb://mindmesh.db"
DEBUG Enable debug logging false

Architecture

The server architecture consists of:

  1. MCP Server Layer: Implements the Model Context Protocol (2025-03-26 specification)
  2. WebContainer Layer: Provides sandboxed environment for execution
  3. PGLite Vector Database: Stores state vectors with pgvector extension
  4. Claude Swarm Layer: Manages multiple specialized Claude instances
  5. Quantum Field Layer: Handles field coherence and optimization
  6. Embedding Layer: Generates high-quality embeddings using VoyageAI models

Requests flow through these layers as follows:

Client Request → MCP Server → Swarm Processing → Claude API → Coherence Optimization → Response

Advanced Features

Web Container Integration

The server uses WebContainer technology for a fully sandboxed environment, providing:

  • Isolated execution environment
  • Full stack capabilities
  • File system access
  • Network communication

PGLite with Vector Extension

PGLite provides:

  • Client-side PostgreSQL database compiled to WebAssembly
  • Vector operations through pgvector extension
  • Live query notifications for real-time updates
  • Persistent storage across sessions

Field Coherence Optimization

The coherence optimization system:

  1. Processes a query through multiple specialized Claude instances
  2. Generates state vectors for each response
  3. Calculates coherence metrics between instances
  4. Selects the most coherent output
  5. Maintains a dynamic field state in the vector database

VoyageAI Embeddings

The server uses VoyageAI's state-of-the-art embedding models for:

  • High-quality state vector generation
  • More accurate coherence calculations
  • Better field modeling and optimization

When VoyageAI API key is not available, the server falls back to a simpler, deterministic embedding method.

Development

Project Structure

  • src/index.ts: Main entry point
  • src/server.ts: Core server implementation
  • .env: Configuration file
  • package.json: Dependencies and scripts

Building

npm run build

This will compile TypeScript to JavaScript in the dist directory.

Testing

npm test

License

MIT

Acknowledgements

This project uses the following technologies:

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    Reviews

    3 (1)
    Avatar
    user_RI4Ih8ls
    2025-04-16

    I've been using mcp-mindmesh by wheattoast11, and it's a fantastic tool! The user-friendly interface and robust features make it an essential part of my daily workflow. I highly recommend it to anyone looking to streamline their tasks and enhance productivity. Check it out on GitHub!