mcp-community

This MCP server provides a Model Context Protocol interface implemented in Python under the Python section of the project. The README indicates there is a Python implementation (with documentation linked at python/README.md) and a TypeScript version that is coming soon. To use the server, install the Python runtime and the project dependencies, then start the server via the Python module entry point. The server exposes the MCP protocol endpoints and tooling to interact with language models and context windows in a standardized way. Once running, you can utilize the Python-based MCP tools to register models, configure contexts, and exchange messages following the MCP specification. Because the TypeScript version is noted as coming soon, the primary tooling currently available will be the Python implementation.

Prerequisites:

• Python 3.8+ (recommended 3.10+)
• pip (bundled with Python)
• Git

Install and run:

1. Clone the repository: git clone https://github.com/your-org/mcp-community.git
2. Navigate to the Python section: cd mcp-community/python
3. Create a virtual environment (optional but recommended): python -m venv venv source venv/bin/activate # (Linux/macOS) venv\Scripts\activate # (Windows)
4. Install dependencies: pip install -r requirements.txt
5. Run the MCP Python module: python -m mcp_community
6. Access the server endpoints as documented in python/README.md (see the Python readme link in the project).

Note: The TypeScript implementation is noted as coming soon, so current usage is focused on the Python version.

Tips and considerations:

• The mcp_config section in this documentation uses a Python module entry point suggesting a module named mcp_community provides the MCP server interface.
• If you encounter port or binding issues, check environment variables or configuration files referenced in the Python README (e.g., host, port, and log level).
• Since the TypeScript version is labeled as coming soon, keep an eye on the repository for updates if you require a Node/TS-based client or server.
• Ensure your Python virtual environment is activated when installing dependencies and running the server to avoid conflicts with system packages.