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.

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  • Why this server?

    Built with FastAPI to provide a lightweight MCP server for ODBC database connections.

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    Provides SQLAlchemy (via pyodbc) connectivity to any Database Management System (DBMS) that's accessible via SQLAlchemy.
    11
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    Apache 2.0
    • Apple
    • Linux
  • Why this server?

    Utilized as the server framework to expose SymPy's mathematical computation capabilities through an API accessible via the MCP protocol.

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    A mathematical computation service that enables users to perform symbolic calculations including basic arithmetic, algebra, calculus, equation solving, and matrix operations through the MCP protocol.
    1
    1
    Python
    MIT License
  • Why this server?

    Provides a REST API interface using FastAPI with endpoints for creating, retrieving, updating, and deleting error records

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    An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.
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    2
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    MIT License
    • Apple
  • Why this server?

    Converts FastAPI endpoints to Postman collections, enabling automatic synchronization of API definitions with Postman for documentation and testing.

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    Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.
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  • Why this server?

    Powers the backend API that handles image processing and recommendation requests for the fashion recommender system.

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    A CLIP-Based Fashion Recommender system that allows users to upload clothing images and receive tags and recommendations based on visual analysis.
    1
    Python
    Apache 2.0
  • Why this server?

    Automatically exposes FastAPI endpoints as Model Context Protocol (MCP) tools, preserving schemas and documentation

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    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.
    2,821
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    MIT License
    • Linux
    • Apple
  • Why this server?

    Uses FastAPI to provide REST API endpoints for YARA scanning, rule management, and file operations, with interactive API documentation.

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    A Model Context Protocol server that enables AI assistants to perform YARA rule-based threat analysis on files and URLs, supporting comprehensive rule management and detailed scanning results.
    10
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    MIT License
    • Linux
    • Apple
  • Why this server?

    Provides an HTTP API server implementation with endpoints for listing tools, calling individual tools, and executing sequences of tools for Fusion 360 operations.

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    A Model Context Protocol server that enables Cline to translate natural language prompts into Fusion 360 CAD operations by mapping commands to Fusion's API and generating executable Python scripts.
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    MIT License
  • Why this server?

    Built on FastAPI to provide a web API interface for BurpSuite functionality, with Swagger UI and ReDoc documentation available.

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    BurpSuite MCP Server: A powerful Model Context Protocol (MCP) server implementation for BurpSuite, providing programmatic access to Burp's core functionalities.
    12
    Python
    MIT License
  • Why this server?

    Serves as the API framework for the MCP server, providing documentation at /docs endpoint and RESTful endpoints for tool invocation.

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    An MCP server that enables AI agents to interact with Modal, allowing them to deploy apps and run functions in a serverless cloud environment.
    Python
    MIT License
  • Why this server?

    Uses FastAPI as the backend framework to serve the MCP server endpoints

  • Why this server?

    Powers the REST, GraphQL, and WebSocket API interfaces, enabling different methods of interacting with the AI models through standardized endpoints.

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    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.
    5
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    MIT License
  • Why this server?

    The MCP server is implemented using the FastAPI framework, providing a web application with both MCP and standard web endpoints.

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    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.
    9
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    MIT License
  • Why 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

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    An MCP server that exposes HTTP methods defined in an OpenAPI specification as tools, enabling interaction with APIs via the Model Context Protocol.
    2
    Python
    MIT License
  • Why this server?

    Used in the example workflow to design and implement a Todo app, with the MCP server tracking components and providing consistent implementation guidance.

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    Creates and maintains a semantic knowledge graph of code that allows maintaining context across sessions with Claude, providing advanced search capabilities without requiring the entire codebase in the context window.
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    Python
    • Apple
  • Why this server?

    Provides the API framework for the MCP server with JWT authentication support for secure user access.

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    A conversational application server that integrates LLM capabilities via Ollama with vector memory context, supporting multiple users, sessions, automatic history summarization, and a plugin system for executing real actions.
    Python
  • Why this server?

    Implements a server with MCP endpoints using FastAPI, providing a way to expose the vector database retrieval functionality via API.

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    A Machine Conversation Protocol server that enables AI agents to perform Retrieval-Augmented Generation by querying a FAISS vector database containing Sui Move language documents.
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    • Linux
  • Why this server?

    Supports integration with FastAPI for running the MCP server, providing both standalone and integrated deployment options

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    A server that helps people access and query data in databases using the Query Runner with integration of the Model Context Protocol (MCP) Python SDK. Support databases including PostgreSQL Redshift MySQL Microsoft SQL Server Google APIs Amazon Web Services (via boto3) CockroachDB SQLite
    6
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    GPL 3.0
    • Linux
    • Apple
  • Why this server?

    Provides the backend framework for the MCP server implementation

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

    Uses FastAPI to create a REST API server that handles requests for managing conversation context and interacting with language models.

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    A system that manages context for language model interactions, allowing the model to remember previous interactions across multiple independent sessions using Gemini API.
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    • Apple
  • Why this server?

    Used for implementing test endpoints and API functionality for the MCP server, enabling proper API interaction with Databricks services.

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    A server that implements the Model Completion Protocol (MCP) to allow LLMs to interact with Databricks resources including clusters, jobs, notebooks, and SQL execution through natural language.
    6
    Python
  • Why this server?

    Powers the server's backend API and WebSocket communication, enabling real-time interaction between the multi-agent system and client applications

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    A multi-agent human-computer interaction system that enables natural interaction through integrated visual recognition, speech recognition, and speech synthesis capabilities.
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    • Apple
  • Why this server?

    Powers the server's API framework, exposing endpoints for file access, database operations, and vector search capabilities

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    A multi-functional computing platform server designed to integrate with large language models like Qwen, providing file access, database connections, API integration, and vector database functionality.
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  • Why this server?

    Uses FastAPI as the web framework for implementing the MCP server API endpoints

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    A server implementation that provides a unified interface for OpenAI services, Git repository analysis, and local filesystem operations through REST API endpoints.
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  • Why this server?

    Powers the underlying server architecture for the MCP implementation.

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    A server implementing the Model Context Protocol that enables users to retrieve LinkedIn profile information and activity data via EnrichB2B API, and generate text using OpenAI GPT-4 or Anthropic Claude models.
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    • Linux
  • Why this server?

    Integrates with a FastAPI hosted ML server to serve a trained Random Forest model for predictions and data processing.

  • Why this server?

    Used for API implementation in the backend technical stack

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    A robust SSH server facilitating secure remote command execution with TMUX session management, multi-window support, and smart session recovery for improved AI-human interaction.
    4
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  • Why this server?

    Uses FastAPI as the foundation for the server implementation, providing high-performance API endpoints and asynchronous request handling for the MCP protocol.

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    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.
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  • Why this server?

    Uses FastAPI for the HTTP server implementation with SSE transport for connecting to Claude and Cursor.

  • Why 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.

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    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).
    13
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  • Why this server?

    The server uses FastAPI for its backend to handle requests and integrate with the PokeAPI database

  • Why this server?

    Used as the web framework for implementing the MCP server's API endpoints for bird detection data.

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    A 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.
    3
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    • Linux
    • Apple