"mcp server fetch" matching MCP servers:

A server based on Model Context Protocol that parses Swagger/OpenAPI documents and generates TypeScript types and API client code for different frameworks (Axios, Fetch, React Query).

An MCP server providing read-only access to Linear issues for language models, allowing them to fetch issue details and comments using a Linear API token.

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.

Enables AI agents to connect to any GraphQL endpoint, introspect schemas, and execute queries or mutations through auto-generated tools.

Parses Swagger 2.0 and OpenAPI 3.x specifications, exposing API endpoints, schemas, and authentication through MCP tools with local caching to reduce token usage.

Optimizes REST API calls for AI agents by returning compact schemas instead of full responses, allowing agents to fetch only needed fields via jq masks, reducing token consumption by up to 50x.

Enables load testing and validation of an order API by generating synthetic orders, previewing them, and sending batches while enforcing guardrails like bounded counts and fixed seeds for replay.

MCP server that exposes RESTForge capabilities to AI agents, enabling them to set up, configure, generate code, and manage RESTForge projects through natural language.

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

Enables AI assistants to explore and interact with the Facets Control Plane API via natural language, supporting operations like searching endpoints, loading schemas, and making authenticated API calls.

MCP server for reading, writing, and organizing API documentation in Apidog.

A read-only API change deploy gate for AI coding agents that analyzes OpenAPI specs to determine if changes are safe to deploy. It provides tools for comparing specs, explaining breaking changes, and generating migration guides.

A read-only MCP server that exposes Automeli's public API documentation (v2 canonical, v1 frozen) to LLMs via fetch and cache over www.automeli.com artifacts. It enables listing, searching, and retrieving endpoints, OpenAPI specs, error explanations, code snippets, and end-to-end flow guides.

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

An MCP server for interacting with Treasure Data API, allowing users to retrieve database information and check server status through natural language queries.

Enables AI assistants to fetch and understand API endpoint definitions from Apifox projects in real-time. Supports retrieving complete API specifications including request methods, parameters, headers, and response schemas to improve development efficiency and code generation quality.

A generic MCP server that dynamically exposes any OpenAPI-documented REST API to LLMs by auto-discovering endpoints. It provides tools for exploring API capabilities and making authenticated requests directly through natural language interfaces.

Enables MCP hosts to list, look up, and describe a static catalog of OpenAPI operations, and to inspect a governing contract and explicit deny-list that define what the server refuses to do.

Provides AI-enabled access to Amazon Business API documentation, sample code, and troubleshooting resources. Enables developers to search and retrieve API documentation, generate integration code, and get guided solutions for common errors during the API integration process.

Enables interaction with Webhook.site to create, manage, and monitor endpoints for capturing HTTP requests, emails, and DNS lookups. It provides 16 tools for testing webhooks and inspecting incoming data through the Model Context Protocol.