MCP Servers for FastAPI
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.
Why this server?
Powers the REST, GraphQL, and WebSocket API interfaces, enabling different methods of interacting with the AI models through standardized endpoints.
-securityAlicense-qualityA high-performance FastAPI server supporting Model Context Protocol (MCP) for seamless integration with Large Language Models, featuring REST, GraphQL, and WebSocket APIs, along with real-time monitoring and vector search capabilities.5PythonMIT LicenseWhy this server?
Automatically exposes FastAPI endpoints as Model Context Protocol (MCP) tools, preserving schemas and documentation
-securityAlicense-qualityA zero-configuration tool that automatically exposes FastAPI endpoints as Model Context Protocol (MCP) tools, allowing LLM systems like Claude to interact with your API without additional coding.120PythonMIT LicenseWhy this server?
The MCP server is implemented using the FastAPI framework, providing a web application with both MCP and standard web endpoints.
-securityAlicense-qualityA Server-Sent Events implementation using FastAPI framework that integrates Model Context Protocol (MCP), allowing AI models to access external tools and data sources like weather information.6PythonMIT LicenseWhy this server?
Mentioned in the example configuration where a FastAPI server is running, and the README notes it uses a FastMCP server with registered tools
-securityAlicense-qualityAn MCP server that exposes HTTP methods defined in an OpenAPI specification as tools, enabling interaction with APIs via the Model Context Protocol.2PythonMIT LicenseWhy this server?
Uses FastAPI as the backend framework to serve the MCP server endpoints
-securityAlicense-qualityThis server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.10PythonMIT LicenseWhy this server?
Integrates with a FastAPI hosted ML server to serve a trained Random Forest model for predictions and data processing.
-securityFlicense-qualityA server that integrates trained Random Forest models with Bee Framework, enabling ReAct interactivity for AI tools and agents.9PythonWhy this server?
Uses FastAPI as the web framework for implementing the MCP server API endpoints
-securityFlicense-qualityA server implementation that provides a unified interface for OpenAI services, Git repository analysis, and local filesystem operations through REST API endpoints.PythonWhy this server?
Used for API implementation in the backend technical stack
-securityFlicense-qualityA robust SSH server facilitating secure remote command execution with TMUX session management, multi-window support, and smart session recovery for improved AI-human interaction.3PythonWhy this server?
The MCP server is built on FastAPI, leveraging its ecosystem for automatic OpenAPI documentation generation, dependency injection, middleware support, validation, and async capabilities.
-securityFlicense-qualityA production-ready MCP server built with FastAPI, providing an enhanced tool registry for creating, managing, and documenting AI tools for Large Language Models (LLMs).12PythonWhy this server?
The server uses FastAPI for its backend to handle requests and integrate with the PokeAPI database
PythonWhy this server?
Used as the web framework for implementing the MCP server's API endpoints for bird detection data.
-securityFlicense-qualityA Python-based server that enables accessing and analyzing bird detection data through the Model Context Protocol, offering features like filtering detections, accessing audio recordings, and generating reports.3Python