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?
Built with FastAPI to provide a lightweight MCP server for ODBC database connections.
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?
Utilized as the server framework to expose SymPy's mathematical computation capabilities through an API accessible via the MCP protocol.
Why this server?
Provides a REST API interface using FastAPI with endpoints for creating, retrieving, updating, and deleting error records
Why this server?
Built with FastAPI to provide web API endpoints for all txtai functionality
Why this server?
Converts FastAPI endpoints to Postman collections, enabling automatic synchronization of API definitions with Postman for documentation and testing.
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?
Supports integration with FastAPI for running the MCP server, providing both standalone and integrated deployment options
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?
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?
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?
Automatically exposes FastAPI endpoints as Model Context Protocol (MCP) tools, preserving schemas and documentation
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 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 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?
Serves as the backend framework providing API endpoints for the hotel management system
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?
Uses FastAPI to implement the server's API, enabling tools and resources for Excel operations through HTTP endpoints.
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?
Provides the API framework for the MCP server with JWT authentication support for secure user access.
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 backend API and WebSocket communication, enabling real-time interaction between the multi-agent system and client applications
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.