bitfollow/mcp-server-example
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This repository contains an implementation of a Model Context Protocol (MCP) server for educational purposes, demonstrating how to build a functional MCP server that can integrate with various LLM clients.
The Model Context Protocol (MCP) server is designed to standardize the way applications provide context to Language Model Models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing AI models to interface with different data sources and tools seamlessly. The MCP server follows a client-server architecture, enabling host applications like IDEs or AI tools to access data through standardized protocols. It supports integration with both local and remote data sources, offering flexibility in switching between LLM providers. The server is lightweight and exposes specific capabilities through the MCP, ensuring secure data handling within infrastructures. The implementation is built using Python and requires the MCP SDK and `uv` package manager for setup.
Features
- Standardized Protocol: Provides a universal way to connect AI models to various data sources.
- Client-Server Architecture: Supports multiple connections with host applications and clients.
- Integration Flexibility: Allows easy switching between different LLM providers and vendors.
- Secure Data Handling: Implements best practices for securing data within infrastructures.
- Lightweight Implementation: Designed to be efficient and easy to deploy.
