Model Context Protocol (MCP) Agent Frameworks Demo

What is the Model Context Protocol (MCP) Agent Frameworks Demo?

The Model Context Protocol (MCP) Agent Frameworks Demo is a repository that showcases the usage of a simple MCP server integrated with various agent frameworks, including Google ADK, LangGraph, OpenAI Agents, and Pydantic-AI Agents.

How to use the MCP Agent Frameworks?

To use the MCP Agent Frameworks, clone the repository, set up your environment variables in a .env file, and run any of the sample scripts provided in the basic_mcp_use directory. For example, you can run uv run basic_mcp_use/pydantic_mcp.py which requires a GEMINI_API_KEY.

Key features of the MCP Agent Frameworks?

• Demonstrates integration with multiple LLM agent frameworks.
• Provides a simple MCP server for context management.
• Includes tracing capabilities through Logfire for observability.

Use cases of the MCP Agent Frameworks?

1. Building AI applications that require context management for LLMs.
2. Monitoring and tracing LLM agent interactions using Logfire.
3. Facilitating the development of interoperable AI solutions across different LLM providers.

FAQ from the MCP Agent Frameworks?

• What is the Model Context Protocol (MCP)?

MCP is a standardized interface that allows applications to provide context for LLMs, simplifying the development process and enhancing interoperability.

• How do I set up the environment for MCP?

Clone the repository, install required packages, and set up your environment variables in a .env file.

• Can I use different LLM providers with MCP?

Yes! MCP allows you to switch between different LLM providers without overhauling your tool and data integrations.