"FastAPI" matching MCP servers:

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

A production-ready MCP server built with FastAPI, providing an enhanced tool registry for creating, managing, and documenting AI tools for Large Language Models (LLMs).

Enables interaction with Supabase databases and n8n workflows through a JSON-RPC 2.0 MCP server. Provides database operations, vector search capabilities, and webhook-based workflow automation with secure API token authentication.

A Model Context Protocol (MCP) server that enables Large Language Models to interact with and query the classic Northwind database through a REST API.

Provides RAG-based FastAPI documentation retrieval and project introspection tools via MCP, enabling LLMs to query reference docs, symbols, and project OpenAPI specs.

An enterprise-grade Model Context Protocol server for high-performance web analysis that discovers subpages, provides AI-based page summaries, and extracts structured content for RAG using FastMCP and FastAPI.

A 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.

Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.

A local Retrieval-Augmented Generation system that enables AI agents to query and retrieve information from document collections using ChromaDB vector search and Ollama LLMs through a FastAPI interface.

Enables MCP clients to connect to LLM/API services using the Model Context Protocol, providing real-time interaction and tool access. Also offers RESTful API endpoints via FastAPI for programmatic integration with existing systems.

A modular, extensible FastAPI-based platform that aggregates multiple AI tools and microservices into a unified interface with standardized I/O formats, perfect for frontend integration or LLM system orchestration.

A FastAPI-based MCP server that enables LLM agents to interact with Ollama models through standardized MCP tools, with optional MySQL and Redis integration for data persistence and caching.

An MCP-compatible RAG backend using LangGraph and FastAPI, enabling chaining of AI model logic with document context search.

Exposes LangChain agent capabilities through the Model Context Protocol, enabling multi-step reasoning tasks with ReAct pattern execution via a production-ready FastAPI service deployed on Google Cloud Run.

Enables searching through vectorized Cursor IDE chat history via a FastAPI service powered by LanceDB and Ollama.

Modular monolithic FastAPI shared AI service platform providing config center, prompt registry, LLM gateway, RAG service, secret manager, tool registry, and MCP server wrapper.

Enables routing of ML tasks like chat, sentiment analysis, recommendations, and summarization to appropriate models through a dynamic YAML-based registry. Provides async FastAPI endpoints with streaming support, retry logic, and pluggable model architecture for scalable ML inference.

A FastAPI-based application that enables document embedding and semantic retrieval using Qdrant vector database, allowing users to convert documents into embeddings and retrieve relevant content through natural language queries.

A simple application demonstrating Model Context Protocol (MCP) integration with FastAPI and Streamlit, allowing users to interact with LLMs through a clean interface.

A modern Model Control Plane (MCP) project that provides a lightweight, extensible foundation for building and deploying intelligent systems that manage and expose AI/LLM capabilities through Python, FastAPI, and Docker.