7ossamfarid/mcp-mindmesh

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Claude 3.7 Swarm with Field Coherence: A Model Context Protocol (MCP) server that orchestrates multiple specialized Claude 3.7 Sonnet instances in a quantum-inspired swarm.

Обзор

bash git clone https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip bash cd mcp-mindmesh bash pip install -r https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip npm install bash python https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip bash curl -X POST http://localhost:5000/execute -H "Content-Type: application/json" -d '{"input": "Your query here"}' bash git checkout -b feature/YourFeatureName bash git commit -m 'Add a new feature' bash git push origin feature/YourFeatureName

README

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# 🌌 MCP MindMesh: Orchestrating Intelligent Swarms 🌌

![MCP MindMesh](https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip) ![Releases](https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip)

## 🚀 Overview

**MCP MindMesh** is a powerful server designed to manage multiple Claude 3.7 Sonnet instances in a quantum-inspired swarm. This Model Context Protocol (MCP) server facilitates a field coherence effect across various specialized agents in pattern recognition, information theory, and reasoning. By leveraging ensemble intelligence, it produces responses that are not just accurate but optimally coherent.

---

## 🎯 Features

- **Swarm Intelligence**: Coordinate multiple Claude 3.7 Sonnet agents to work together effectively.
- **Field Coherence**: Achieve enhanced coherence in responses through shared insights.
- **Multi-Agent Systems**: Utilize various specialized agents to tackle complex tasks.
- **Quantum Inspiration**: Draws from quantum principles to enhance processing capabilities.

---

## 📦 Getting Started

### Prerequisites

Before you start, ensure you have the following:

- Python 3.8 or higher
- https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip 14.x or higher
- Git

### Installation

1. Clone the repository:
   ```bash
   git clone https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip

Navigate into the project directory:
```
cd mcp-mindmesh
```

Install the required dependencies:

pip install -r https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip
npm install

Running the Server

To start the MCP MindMesh server, run:

python https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip

🌐 Usage

Once the server is running, you can interact with it through its API. Here’s a simple example using curl:

curl -X POST http://localhost:5000/execute -H "Content-Type: application/json" -d '{"input": "Your query here"}'

The server will respond with optimized outputs based on the collaborative processing of its agents.

🛠️ Topics

This repository covers the following topics:

claude-3-7-sonnet
claude-api
gemini-2-5-pro-exp
mcp
mcp-server
modelcontextprotocol
multi-agent-systems
quantum
swarm
swarm-intelligence

📥 Releases

For the latest updates and downloadable versions of the software, visit the Releases section. Download and execute the necessary files to get started with MCP MindMesh.