mcp-server-sample

mcp-server-sample

3.3
developer_tools

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This repository contains an implementation of a Model Context Protocol (MCP) server for educational purposes, demonstrating integration with various LLM clients.

The Model Context Protocol (MCP) server is designed to standardize how applications provide context to large language models (LLMs). It acts as a bridge, allowing AI models to connect seamlessly with different data sources and tools. The MCP server follows a client-server architecture, enabling host applications like IDEs or AI tools to access data through standardized protocols. It supports three main capabilities: resources, tools, and prompts, which facilitate data access, function execution, and task completion, respectively. The server is lightweight and can connect to both local and remote data sources, providing flexibility and security in data handling. The MCP server is built using Python and requires the MCP SDK and `uv` package manager for setup.

Features

  • Standardized Protocol: Provides a unified way to connect AI models to various data sources.
  • Client-Server Architecture: Supports multiple connections with host applications and clients.
  • Flexible Integration: Allows switching between different LLM providers and vendors.
  • Security Best Practices: Ensures data security within the infrastructure.
  • Pre-built Integrations: Offers a growing list of integrations for direct LLM connectivity.

Tools

  1. MCP Inspector

    Tools for testing MCP servers

  2. Claude Desktop

    Tools that can install and interact with MCP servers

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