FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.
Why this server?
Implemented using FastAPI to provide both SSE and HTTP streaming endpoints for clients to interact with the MCP protocol, supporting tool calls and prompt interactions.
Why this server?
Includes a FastAPI server as an alternative interface with interactive API documentation (Swagger UI and ReDoc) for direct HTTP access
Why this server?
Utilized as the server framework to expose SymPy's mathematical computation capabilities through an API accessible via the MCP protocol.
Why this server?
Built with FastAPI to provide a lightweight MCP server for ODBC database connections.
Why this server?
Provides a REST API interface using FastAPI with endpoints for creating, retrieving, updating, and deleting error records
Why this server?
Generates mock API servers using FastAPI as the framework, complete with middleware, admin UI, and logging capabilities
Why this server?
Used as the web framework for potential future REST API functionality within the MCP server.
Why this server?
Converts FastAPI endpoints to Postman collections, enabling automatic synchronization of API definitions with Postman for documentation and testing.
Why this server?
Uses FastAPI to build the MCP server, providing a robust HTTP-based interface for context management operations.
Why this server?
Uses FastAPI to expose endpoints for the MCP protocol and health checks, enabling communication with AI clients
Why this server?
Uses FastAPI to provide REST API endpoints for YARA scanning, rule management, and file operations, with interactive API documentation.
Why this server?
Uses FastAPI as the web framework for building the API, providing automatic API documentation generation, schema validation, and type safety for the MLB data endpoints.
Why this server?
Employs FastAPI for the backend service that handles document ingestion, validation, and RAG pipeline orchestration.
Why this server?
Built with FastAPI to provide web API endpoints for all txtai functionality
Why this server?
Powers the microservice API, providing endpoints for job URL analysis and company profile generation.
Why this server?
Serves as the framework for exposing the MCP server's functionality via HTTP APIs, providing standardized endpoints for integration with other applications.
Why this server?
Provides a Model Context Protocol (MCP) interface for FastAPI endpoints, automatically generating tools from API endpoints decorated with @mcp_app.tool(), enabling interaction with CRUD operations through MCP clients
Why this server?
Powers the main web application routing and HTTP request handling, including administrative API endpoints and OAuth callback processing.
Why this server?
Automatically exposes FastAPI endpoints as Model Context Protocol (MCP) tools, preserving schemas and documentation
Why this server?
Powers the backend API that handles image processing and recommendation requests for the fashion recommender system.
Why this server?
Uses FastAPI as the backend framework for serving the CLIP-based fashion recommendation system, handling image uploads and providing recommendation endpoints.
Why this server?
Implements the MCP server using FastAPI endpoints, exposing system monitoring tools through fastapi-mcp
Why this server?
Provides a FastAPI-based web server that exposes Beijing car quota lottery search functionality through standardized API endpoints
Why this server?
Serves as the foundation for the MCP server, exposing CRUD endpoints through FastAPI-MCP that allows AI agents to interact with the item database
Why this server?
Recognized and recommended as a framework for Python API projects with Pydantic for validation within project contexts
Why this server?
Uses FastAPI to provide a REST API interface compatible with OpenAI's chat completion API
Why this server?
Powers the server's backend API and WebSocket communication, enabling real-time interaction between the multi-agent system and client applications
Why this server?
Provides a web interface for managing PDF files, allowing users to upload, download, and view PDF files through a FastAPI-based web UI
Why this server?
Supports integration with FastAPI for running the MCP server, providing both standalone and integrated deployment options
Why this server?
Uses FastAPI to expose the Bayesian MCP server API endpoints for model creation, belief updating, prediction generation, model comparison, and visualization.
Why this server?
Integrates with FastAPI framework to provide high-performance server-side events (SSE) communication and schema validation capabilities for Model Context Protocol implementations
Why this server?
Uses FastAPI as the web framework to implement the MCP server endpoints and API functionality.
Why this server?
Powers the REST interface for the document processing system, enabling API-based interactions with the document processing capabilities.
Why this server?
Server is built on FastAPI framework, providing HTTP endpoints for SmartScreen control and integration
Why this server?
Used as the web framework to build the MCP server API endpoints
Why this server?
Built on FastAPI to provide a web API interface for BurpSuite functionality, with Swagger UI and ReDoc documentation available.
Why this server?
Automatically exposes FastAPI endpoints as MCP tools, preserving schemas and documentation from the original API. Allows seamless integration of any FastAPI application with MCP clients without additional configuration.
Why this server?
Provides a lightweight server implementation that exposes an endpoint to execute shell commands and stream their output in real-time.
Why this server?
Uses FastAPI as the web framework for implementing the MCP server API endpoints
Why this server?
Uses FastAPI as the backend framework to serve the MCP server endpoints
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.
Why this server?
Serves as the API framework for the MCP server, providing documentation at /docs endpoint and RESTful endpoints for tool invocation.
Why this server?
Powers the REST, GraphQL, and WebSocket API interfaces, enabling different methods of interacting with the AI models through standardized endpoints.
Why this server?
The MCP server is implemented using the FastAPI framework, providing a web application with both MCP and standard web endpoints.
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
Why this server?
Implements the Model Context Protocol server using FastAPI framework, providing a discoverable, versioned API for exposing herd data.
Why this server?
Offers FastAPI routing documentation with examples and implementation guidance
Why this server?
Built on FastAPI framework, providing performant REST endpoints for context retrieval, model listing, and health checking.
Why this server?
Used to create a multi-tool MCP server that can host multiple tools in a single endpoint
Why this server?
Implements the control layer using FastAPI to manage requests between the UI and model layer, handling validation, preprocessing, and error handling.
Why this server?
Provides a high-performance API backend with OpenAPI documentation for the MCP server
Why this server?
Serves as the web framework for the MCP API, providing the RESTful endpoints for monitor management and other UptimeRobot operations
Why this server?
Uses FastAPI to create an MCP server that exposes the Northwind database through both a REST API and an MCP endpoint, allowing queries for product data and other Northwind dataset information.
Why this server?
Powers the MCP Gateway with a robust API framework, enabling tool routing and request handling.
Why this server?
Used as the server framework to implement the SSE transport for the MCP server
Why this server?
Implements an async high-performance API server using FastAPI, enabling real-time train ticket queries with SSE streaming protocol support
Why this server?
Implements the MCP server using FastAPI to expose GoHighLevel sub-account tools
Why this server?
Powers the backend API server that handles routing user questions to appropriate specialized agents
Why this server?
Provides a specialized REST API client with Swagger documentation for development and testing of LinkedIn functionality, offering endpoints for profile management, content creation, and networking.
Why this server?
Provides the underlying web framework for exposing math tools and prompt templates via Server-Sent Events (SSE)
Why this server?
Powers the RESTful API interface, offering clean, well-documented endpoints for AI model interactions.
Why this server?
Uses FastAPI for the web framework and RESTful API support, providing device management interfaces and WebSocket functionality for real-time communication.
Why this server?
Provides the API backend for the MCP server, allowing HTTP-based interactions with the system's microservices
Why this server?
Powers the web server that connects to the MCP server and handles client requests from the htmx UI.
Why this server?
Provides a web user interface with a friendly dashboard for interacting with datasets, viewing results, and controlling the autonomous analyst workflow.
Why this server?
Uses FastAPI to create the server endpoints that expose the MCP protocol interfaces for tool discovery and execution.
Why this server?
Built on the FastAPI framework for creating the MCP server API endpoints that interface with PostgreSQL databases.
Why this server?
Provides the backend framework that handles API requests, PDF processing, and vector storage operations
Why this server?
Provides the server framework for the MCP implementation, exposing endpoints for tool discovery and JSON-RPC calls to interact with the to-do list application.
Why this server?
Implements a FastAPI server that exposes Berghain events data as API endpoints and MCP tools for AI agents
Why this server?
Powers the backend API of the MCP server, enabling management functionality through a RESTful interface
Why this server?
Implements the MCP server using FastAPI as the framework, providing endpoints for payment creation and status verification that bridge Claude with the Gotas Commerce API.
Why this server?
Exposes API endpoints for health checks, service discovery, natural language command processing, and direct command execution through a REST interface
Why this server?
Provides the foundation for the MCP Gateway, transforming FastAPI endpoints into MCP tools that allow LLMs to interact with corporate APIs in a controlled manner.
Why this server?
Built on FastAPI to provide REST API endpoints for document embedding and semantic retrieval capabilities
Why this server?
Uses FastAPI to implement the Model Context Protocol server with Server-Sent Events for streaming communication
Why this server?
Provides the API framework for the MCP server with JWT authentication support for secure user access.
Why this server?
Serves as the backend framework providing API endpoints for the hotel management system
Why this server?
Built with FastAPI to provide a robust API framework for generating Master Content Plans
Why this server?
Provides the asynchronous API framework for handling image generation and editing requests
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.
Why this server?
Provides a FastAPI-based server implementation that exposes cat facts data through SSE transport, complete with automatic OpenAPI documentation.
Why this server?
Provides a web interface and JSON API endpoints for accessing the TPC data, allowing users to browse thoughts, plans, and changes via a simple HTML interface.
Why this server?
Implements a REST API with CORS support and structured JSON responses for easy frontend integration.
Why this server?
Used as the web framework for implementing MCP-compatible REST endpoints, exposing agent personality traits and callable tools through standardized HTTP interfaces.
Why this server?
The server can run as a FastAPI-based service with endpoints for API information, health checks, voice listings, and MCP communication.
Why this server?
Provides REST API endpoints for interacting with the supply chain system, including inventory status, AGV management, order creation, and agent queries
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.
Why this server?
Implements a server with MCP endpoints using FastAPI, providing a way to expose the vector database retrieval functionality via API.
Why this server?
Provides the backend framework for the MCP server implementation
Why this server?
Uses FastAPI to create a REST API server that handles requests for managing conversation context and interacting with language models.
Why this server?
Used for implementing test endpoints and API functionality for the MCP server, enabling proper API interaction with Databricks services.
Why this server?
Powers the server's API framework, exposing endpoints for file access, database operations, and vector search capabilities
Why this server?
Powers the underlying server architecture for the MCP implementation.
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
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.
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.