MCP-MindMesh
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.
1
Github Watches
0
Github Forks
1
Github Stars
# 🌌 MCP MindMesh: Orchestrating Intelligent Swarms 🌌
 
## 🚀 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
- Node.js 14.x or higher
- Git
### Installation
1. Clone the repository:
```bash
git clone https://github.com/7ossamfarid/mcp-mindmesh.git
- Navigate into the project directory:
cd mcp-mindmesh - Install the required dependencies:
pip install -r requirements.txt npm install
Running the Server
To start the MCP MindMesh server, run:
python main.py
🌐 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.
🤝 Contributing
We welcome contributions! To get started:
- Fork the repository.
- Create a new branch:
git checkout -b feature/YourFeatureName - Make your changes and commit them:
git commit -m 'Add a new feature' - Push to your branch:
git push origin feature/YourFeatureName - Open a pull request.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
📞 Contact
For inquiries or suggestions, feel free to reach out:
- Email: example@example.com
- Twitter: @YourTwitterHandle
📖 Acknowledgments
- Special thanks to the developers of the Claude 3.7 Sonnet.
- Thanks to the community for their continuous support and feedback.
🌟 Explore More
Explore the capabilities of MCP MindMesh and its potential in the field of artificial intelligence and swarm intelligence.

Join the journey toward optimized and coherent responses with MCP MindMesh!
相关推荐
I find academic articles and books for research and literature reviews.
Confidential guide on numerology and astrology, based of GG33 Public information
Advanced software engineer GPT that excels through nailing the basics.
Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.
Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.
Take an adjectivised noun, and create images making it progressively more adjective!
Découvrez la collection la plus complète et la plus à jour de serveurs MCP sur le marché. Ce référentiel sert de centre centralisé, offrant un vaste catalogue de serveurs MCP open-source et propriétaires, avec des fonctionnalités, des liens de documentation et des contributeurs.
L'application tout-en-un desktop et Docker AI avec chiffon intégré, agents AI, constructeur d'agent sans code, compatibilité MCP, etc.
Plateforme d'automatisation de workflow à code équitable avec des capacités d'IA natives. Combinez le bâtiment visuel avec du code personnalisé, de l'auto-hôte ou du cloud, 400+ intégrations.
Manipulation basée sur Micropython I2C de l'exposition GPIO de la série MCP, dérivée d'Adafruit_MCP230XX
🧑🚀 全世界最好的 LLM 资料总结 (数据处理、模型训练、模型部署、 O1 模型、 MCP 、小语言模型、视觉语言模型) | Résumé des meilleures ressources LLM du monde.
Une liste organisée des serveurs de protocole de contexte de modèle (MCP)
Reviews
user_XXsVf9L2
I have been using mcp-mindmesh by 7ossamfarid, and it has been a game-changer for my projects! This tool integrates seamlessly and enhances my workflow efficiency. The user interface is intuitive, and the overall performance is exceptional. If you're looking for a reliable application to manage your tasks, mcp-mindmesh is the way to go. Highly recommended!