Agent Integration Toolkit
Facilitates the creation of Model Context Protocol (MCP) servers and their integration with any Large Language Model (LLM) for enhanced AI agent capabilities.
Acerca de
This project provides a comprehensive guide and toolkit for developing and integrating Model Context Protocol (MCP) servers with Large Language Models (LLMs). Leveraging FastMCP, it simplifies the creation of custom MCP servers that expose external tools, databases, and services to AI assistants. The integration with LLMs is streamlined through mcp-use, which is compatible with popular frameworks like LangChain, Ollama, and various LLM providers, enabling AI agents to interact with external environments, perform multi-step tasks, and access real-time information. It includes practical examples, such as a weather server and browser automation, demonstrating how to build powerful, context-aware AI agents.
Características Principales
- Build custom MCP Servers with FastMCP for exposing tools and services
- Integrate any LLM with MCP servers using mcp-use (e.g., LangChain, Groq, Ollama)
- Includes examples for browser automation and real-time weather alerts
- Supports both STDIO and SSE (Server-Sent Events) MCP server types
- Streamlined project setup and dependency management with UV
- 1 GitHub stars
Casos de Uso
- Develop context-aware AI assistants (e.g., weather reporters, web scrapers)
- Automate complex multi-step tasks using LLM agents
- Enable LLMs to interact with external tools, databases, and services
