build-python

This MCP server is a Python-based Claude-compatible server that enables you to add tools and integrations for Claude Desktop. It provides a framework to expose custom capabilities—such as a to-do list, database interactions, or image processing—via the MCP protocol so Claude can request context, execute tools, and return results. The server is designed to be run locally or in a development environment and can be extended with new tooling by implementing tool handlers in Python that respond to Claude’s requests.

To use it, install Python dependencies, start the server, and configure Claude to point to your local MCP endpoint. Once running, you can register tools (e.g., a Todo CRUD, database queries, or image editing workflows) and test them through Claude’s tool-calling UI. The project demonstrates how to structure tool handlers, how to format inputs/outputs for MCP, and how to chain multiple tools for complex tasks.

Prerequisites:

• Python 3.8+ installed on your system
• Git to clone the repository
• Optional: virtual environment tool (venv) for isolation

1. Clone the repository:

git clone https://github.com/erictechpro-build-python-mcp-server.git
cd erictechpro-build-python-mcp-server

2. Create and activate a virtual environment (recommended):

• On Windows:

python -m venv venv
venv\Scripts\activate

• On macOS/Linux:

python3 -m venv venv
source venv/bin/activate

3. Install dependencies:

pip install -r requirements.txt

4. Run the MCP server (module-based entry point):

python -m build_python_mcp_server

5. Optional: set environment variables to customize behavior before launching:

export CLAUDE_MCP_API_BASE_URL="https://api.openai.com/v1/claude/mcp"

6. Verify the server is reachable at the configured MCP endpoint (default port and path defined by the module).

Notes and tips:

• The server exposes tools via the MCP protocol; implement handlers in Python to map incoming MCP tool calls to your Python functions.
• Common environment variables include API keys for external services, database URLs, and feature flags. See the module's README for a full list of supported options.
• If Claude cannot connect, ensure your local environment's firewall allows inbound connections to the MCP port and that the module name in -m matches the implemented entry point.
• Use virtual environments to avoid dependency conflicts with system Python.
• For debugging, run the server with verbose logging if supported by the module, and check logs for tool invocation details and error traces.