"FastAPI" matching MCP servers:

Exposes FastAPI reference documentation as MCP tools, enabling LLMs to query FastAPI docs during development for accurate code generation.

Exposes your FastAPI endpoints as Model Context Protocol tools with authentication, preserving schemas and documentation.

Enables inventory management through FastAPI with AI chat powered by Ollama, allowing natural language interaction with PostgreSQL data via MCP for clients like Claude Desktop and VS Code.

A zero-configuration tool that automatically converts FastAPI endpoints into Model Context Protocol (MCP) tools, enabling AI systems to interact with your API through natural language.

Exposes FastAPI endpoints as Model Context Protocol (MCP) tools while preserving existing authentication, schemas, and documentation. It enables seamless integration of FastAPI services into MCP ecosystems using a native ASGI transport layer.

A 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.

Enables AI coding assistants to inspect FastAPI applications, routers, and Pydantic models, including generating TypeScript interfaces and Zod schemas and discovering backend routes without hallucination.

An MCP server that gives Claude Code IDE-level intelligence for FastAPI projects — semantic code navigation, safe renaming, route inspection, dependency trees, and Pydantic model analysis. Instead of Claude reading files blindly, it calls structured tools backed by Jedi (Python language server) and Python's AST.

A FastAPI MCP server that uses Server-Sent Events as a transport layer, providing echo functionality through tools, resources, and prompts.

Demonstrates how to integrate Model Context Protocol with Server-Sent Events (SSE) in a FastAPI web application, including a weather service example with tools for getting forecasts and alerts.

Mounts an MCP server onto FastAPI to let AI agents inspect routes, endpoints, and schemas at runtime.

A high-performance Model Context Protocol (MCP) server designed for large language models, enabling real-time communication between AI models and applications with support for session management and intelligent tool registration.

A production-ready Model Context Protocol server that provides mathematical calculations, time zone information, and message echoing capabilities through both WebSocket and HTTP endpoints. Built with FastAPI for robust API functionality and interactive documentation.

A FastAPI library that provides Model Context Protocol tools for endpoint introspection and OpenAPI documentation, allowing AI agents to discover and understand API endpoints.

A minimal CRUD API for items that exposes FastAPI endpoints as MCP tools, enabling natural language interaction with a database through PydanticAI agents.

A Model Context Protocol server that provides tools for introspecting and analyzing FastAPI applications, including route discovery, model schema extraction, and source code viewing. It enables users to explore API structures, generate documentation, and debug dependency injection hierarchies through natural language.

A REST API built with FastAPI that exposes endpoints via Model Context Protocol (MCP), allowing clients to interact with CRUD operations through MCP interfaces.

A 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.

A minimal MCP server that provides current time functionality with optional formatting. Designed for production deployment on Google Cloud Run with proper JSON-RPC 2.0 implementation.

A comprehensive MCP server providing 21+ tools for mathematical operations, string manipulation, file handling, utilities, and web requests via FastAPI and WebSocket.