BTonny/first_mcp_server
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This documentation provides a guide on setting up and testing a Model Context Protocol (MCP) server using Python, following a tutorial from AO - Software & AI on YouTube.
The Model Context Protocol (MCP) server is a framework designed to facilitate the integration and management of machine learning models within various applications. This server setup is based on a Python implementation, allowing users to create, manage, and test MCP servers efficiently. The server is designed to be flexible and can be integrated into different environments, making it a versatile tool for developers working with machine learning models. The setup process involves initializing the server, configuring it with the necessary commands and arguments, and testing its functionality using various commands and queries. The server can be debugged using the MCP Inspector tool, which provides insights into the server's operations and helps identify any issues.
Features
- Easy Initialization: The server can be easily initialized and configured using simple commands.
- Flexible Integration: The server can be integrated into different environments and directories as needed.
- Command Line Interface: Users can manage and test the server using a command line interface.
- Debugging Tools: The MCP Inspector tool allows for easy debugging and monitoring of the server.
- Support for Latest Integrations: The server supports the latest integrations, such as Chroma DB vector database with Langchain.
Usages
usage with claude
claude mcp add /Users/baw/.local/bin/uv --directory /Users/baw/Desktop/dev/mcp/first_mcp_server run main.py
usage with inspector
npx @modelcontextprotocal/inspector uv run main.py
