"A web framework for building APIs using FastAPI" matching MCP servers:

A middleware system that connects large language models (LLMs) with various tool services through an OpenAI-compatible API, enabling enhanced AI assistant capabilities with features like file operations, web browsing, and database management.

Enables semantic search and discovery of free public APIs from an extensive catalog. Provides embedding-based search over API names and descriptions, plus detailed API information retrieval.

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).

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.

A focused MCP server that provides a single web_search tool for web searches, integrating Tavily and Brave with automatic fallback and key rotation.

A self-hosted MCP server that crawls, indexes, and searches documentation from any website locally, including private sites requiring authentication. It provides hybrid search capabilities and local embedding generation to maintain privacy while keeping AI assistant knowledge up to date.

Enables extracting clean, structured markdown from any URL—stripping nav, ads, and scripts—for RAG pipelines and AI research agents, with pay-per-call micropayments via x402.

MCP server for semantic search over PDF documents using RAG, pgvector, and OpenAI embeddings. Includes a web app for document upload and management.

Provides free web search, content fetching, image search, and deep research via SearXNG, no API keys required.

MCP server for searching web documentation via sitemap.xml, enabling semantic search across multiple documentation sites using Ollama embeddings.

Provides standard MCP tools for web search, page fetching with content extraction, and a combined research workflow that returns sources with excerpts, plus a session resource and fact-check prompt template.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Provides a Google search tool via the Serper API, returning structured results and a summary answer for LLMs like Claude.

MCP server that provides web search via LLM API gateways with server-side search, returning cited answers and multi-provider fallback.

Fetches YouTube transcripts and enables semantic search within them using local embeddings, allowing an LLM to retrieve relevant passages with timestamps.

A fast, dependency-light MCP server that converts web pages into clean Markdown, structured metadata, and classified links for language models.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.