"FastAPI" matching MCP servers:

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.

Enables LLM-powered agents to securely communicate with and orchestrate downstream microservices via FastAPI endpoints exposed as MCP tools.

Enables natural language interaction with FastAPI applications through Google's Gemini AI using MCP tools. Provides CRUD operations for user management and application health monitoring through conversational prompts.

A FastAPI + FastMCP shared-memory gateway in front of Honcho v3 that provides a single shared brain for multiple AI agents to read from and write to, enabling context recall and change logging through bearer-authenticated endpoints.

Enables AI-powered resume scoring and feedback through secure Google OAuth authentication. Provides FastAPI endpoints for resume evaluation with plans for leaderboard visualization and competitive scoring features.

FastAPI-based MCP server integrating YOLOv8 object detection and embedding services, enabling AI agents to analyze images via the Model Context Protocol.

A FastAPI-based implementation of the Model Context Protocol that enables standardized interaction between AI models and development environments, making it easier for developers to integrate and manage AI tasks.

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 Claude to manage algorithmic trading workflows via natural language — maintaining watchlists, classifying market regimes, validating trades against risk rules, and submitting paper orders through a gateway to a FastAPI engine.

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 backend that integrates with ElevenLabs MCP to create an AI agent capable of making outbound calls and delivering friendly, jargon-free tech news updates.

A Model Context Protocol server implementation built with FastAPI that enables AI agent interactions. Provides a structured foundation for building AI-powered applications with proper data validation and modern Python tooling.

Enables querying internal documents via a FastAPI REST API and MCP server, using retrieval-augmented generation and an agentic loop that can invoke tools like document search and calculations.

A FastAPI-based Model Context Protocol server that enables tool discovery, invocation history, and human-in-the-loop interaction workflows. It features a Python client and CLI for managing automated tasks that require manual approval and persistence.

A specialized toolchain that guides AI agents through a structured 'Atomic Development' workflow for building Python FastAPI and Supabase backends. It manages project scaffolding and enforces dependency-ordered generation of database models, API routes, and tests.