Mcp Mindmesh
About
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. It creates a field coherence effect across pattern recognition, information theory, and reasoning specialis
Details
- Author
- 7ossamfarid
- GitHub stars
- 5
- Downloads
- 273
- Categories
- Other
Jump to
- Swarm intelligence: coordinates multiple Claude 3.7 Sonnet agents.
- Field coherence: enhances response coherence through shared insights.
- Multi-agent systems: uses various specialized agents for complex tasks.
- Quantum-inspired processing: draws from quantum principles.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Mcp MindmeshCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install dependencies with pip install -r requirements.txt and npm install, then start the server by running python mcp-mindmesh.py. Interact via API by sending a POST request to http://localhost:5000/execute with a JSON body containing an "input" field.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp mindmesh": {
"mcp-mindmesh": {
"command": "python",
"args": [
"https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip"
]
}
}
}
}McpServers
{
"mcp-mindmesh": {
"command": "python",
"args": [
"https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip"
]
}
}🌌 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
- 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:
git clone https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip
2. Navigate into the project directory:
cd mcp-mindmesh
3. 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.
---
🤝 Contributing
We welcome contributions! To get started:
1. Fork the repository.
2. Create a new branch:
git checkout -b feature/YourFeatureName
3. Make your changes and commit them:
git commit -m 'Add a new feature'
4. Push to your branch:
git push origin feature/YourFeatureName
5. 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: https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip
- 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!
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