FastAPI-MCP
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools with built-in authentication for AI agents.
Overview
FastAPI-MCP is a powerful library designed to bridge the gap between FastAPI applications and AI agents using the Model Context Protocol (MCP). It simplifies the process of exposing your FastAPI endpoints as discoverable and usable tools for AI, requiring minimal code changes to your existing application. This allows AI agents to understand and interact with your services in a standardized and secure manner. The library is built to be FastAPI-native, meaning it integrates seamlessly without acting as a generic converter. It automatically handles authentication by leveraging your existing FastAPI dependencies, preserves request/response schemas, and maintains documentation. This ensures that the transition to an MCP-enabled API is smooth, efficient, and secure, making it an ideal solution for developers looking to enhance their applications with AI agent capabilities.
Pricing
Pros & Cons
Pros
- Extremely easy to get started with only 3 lines of code
- Leverages existing FastAPI authentication mechanisms, reducing duplicate effort
- Maintains FastAPI's native performance and efficiency through ASGI
- Automatically preserves API documentation and schemas, ensuring consistency
- Offers flexible deployment strategies to fit various architectural needs
- Supports the emerging Model Context Protocol standard for AI agent communication
Cons
- Requires an existing FastAPI application, not a standalone solution
- Relies on the adoption and maturity of the MCP standard for its full value
- Specific advanced configurations might require deeper understanding of both FastAPI and MCP
- Primarily focused on Python/FastAPI ecosystem, limiting use for other frameworks
Use Cases
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Best For
- Integrating AI agents with existing FastAPI-based microservices
- Building AI-powered applications that interact with backend APIs
- Exposing specific FastAPI endpoints as tools for large language models (LLMs)
- Developing secure and standardized interfaces for AI agent communication
- Rapid prototyping of AI agent integrations with Python backends
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