"Importing FastMCP from the mcp.server Python Module" matching MCP servers:

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Dynamically generates MCP tools from OpenAPI specifications, enabling AI assistants to interact with any REST API through natural language. Supports multiple APIs with authentication, parameter validation, and integration with Claude Desktop and LangChain.

A demonstration server that automatically generates Model Context Protocol (MCP) servers from OpenAPI specifications, providing seamless integration with FastAPI and supporting various transmission methods like STDIO, HTTP, and SSE.

Enables LLM agents to create, read, update, and delete Webhook.site tokens, list and retrieve captured requests, and manage webhook configurations via the Webhook.site API.

Dynamically creates MCP servers from web API configurations, enabling AI assistants to interact with any REST API, GraphQL endpoint, or web service.

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 Python server implementing the Model Context Protocol that exposes tools for querying external APIs, compatible with Claude Desktop and ChatGPT Desktop.

Enables AI assistants to automatically manage Apifox API documentation by importing OpenAPI/Swagger specifications and exporting existing API structures. Supports batch operations, intelligent deprecation marking, and smart scope detection for partial module imports.

Enables AI assistants to interact with Magic-API development environment, supporting script syntax query, API management, debugging, and knowledge search for efficient development.

Enables AI agents to create webhook URLs, wait for incoming deliveries, inspect payloads, and replay or send signed webhook events to a local handler.

Enables AI assistants to query API documentation from Eolink Apikit instances via the Eolink Open API, supporting listing projects, groups, searching APIs by keyword/path, and retrieving detailed API definitions.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

Run the requests in a Postman collection folder and get structured, assertion-level results back straight from your AI assistant.

A TypeScript-based MCP server that enables testing of REST APIs through Cline. This tool allows you to test and interact with any REST API endpoints directly from your development environment.

Validates OpenAPI specs from files, inline content, or URLs, and generates prompts for agent developers based on the API analysis.

Provides comprehensive documentation for 377 Fortnox API endpoints and 81 resource categories directly from the official OpenAPI specification. It enables users to search, browse, and explore technical endpoint details and data schemas within AI assistants without requiring authentication.

MCP server for Mockzilla. Lets coding agents like Claude Code, Claude Desktop, Cursor and Gemini CLI install the Mockzilla CLI and run API mocks from an OpenAPI spec or a single endpoint. Log in from the agent to deploy hosted mocks on mockzilla.org

Enables MCP agents to create test webhook endpoints, read incoming requests, validate payloads against Hookline validators, and manage mock responses directly from the editor.

Python MCP server for running and inspecting Bruno API collections

MCP server that provides 22 tools to manage Apidog API documentation, including importing OpenAPI specs, exporting, diffing, analyzing, and bulk-editing endpoints.