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?
- Building AI applications that require context management for LLMs.
- Monitoring and tracing LLM agent interactions using Logfire.
- 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
.envfile.
- 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.