"Creating an MCP Server Using an API" matching MCP servers:

An MCP server that generates MCP servers. Give it an API definition - OpenAPI 3.0/3.1 or a Postman collection or extend an existing server - and it scaffolds a complete, runnable, ownable TypeScript or Python MCP server for that collection of APIs.

An MCP server that enables LLMs to make arbitrary HTTP requests (GET, POST, PUT, DELETE, etc.) with custom headers, bodies, and cookies, supporting JSON and error handling.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

Turns an OpenAPI spec into a ready-to-run test harness with local LLM agents: WireMock stubs, contract tests, robustness probes, and chaos scenarios you can switch on and off in a running WireMock.

Enables AI agents to execute HTTP/REST/GraphQL requests against any endpoint, including private VPN hosts and local services, while logging untruncated headers, request bodies, and raw responses into a local SQLite audit history. Agents can then search that history by keyword, date, method, or status, retrieve full details by ID, and export everything to JSON.

Enables validating API responses against expected schemas/JSON and listing OpenAPI endpoints to enforce API contracts between services.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

Bridges with an installed API monitoring application to enable launching and status checks, live background capture, process attach, filter-tree inspection, GUI actions, and opening, validating, decoding, searching, inspecting, exporting, and comparing saved captures and related metadata.

Enables interaction with Nullplatform's API endpoints for managing deployments, scopes, services, and other cloud resources through natural language using the official OpenAPI specification.

Exposes REST API endpoints defined in an OpenAPI Specification as MCP tools, allowing AI models to call them via the ModelContext Protocol.

An MCP server that crawls API documentation websites and exposes their content to AI models, enabling them to search, browse, and reference API specifications.

Turns an OpenAPI specification into a broker-published slot of curated, LLM-ready tools that a human operator reviews, tests, and approves before anything goes live. The resulting tools are declarative and run under the broker's authorization, audit, execution limits, and secret handling.

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

Transforms OpenAPI specs into an MCP server, enabling dynamic API interaction through natural language with automatic authentication and endpoint discovery.

Enables LLMs to make arbitrary HTTP API requests with any method and full control over headers, query parameters, and body.

Enables read-only exploration of YApi projects, categories, and interface docs, and deterministic TypeScript/JavaScript API request function and type generation through a preview-then-apply workflow.

Starter scaffold for a workshop to build an MCP API testing server, intended to be extended through incremental steps.

MCP server for making API calls with authentication support. Allows configuring multiple API endpoints and performing GET, POST, PUT, DELETE requests, including form data and file uploads.

Converts any REST API endpoints into MCP tools, enabling AI clients like Cursor and Claude Desktop to call internal services directly.

Converts REST APIs into MCP tools using Gradio, demonstrated with a local IBM Granite model via Ollama. Enables LLM clients to interact with any REST API endpoint through the MCP protocol.

Dynamically converts any API with an OpenAPI v3 specification into MCP tools for AI assistants. It supports multiple authentication methods including OAuth2, Bearer tokens, and API keys for flexible integration.

A unified local API gateway providing caching, rate limiting, and full Model Context Protocol compatibility for AI agent integration. It enables users to aggregate multiple API endpoints into a single gateway with built-in observability and customizable eviction strategies.

An MCP server for the VTEX Subscriptions API (v3) that enables managing subscription services through natural language interactions, auto-generated using AG2's MCP builder.

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

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.

Enables monitoring chosen API vendors and public URLs, comparing each source with its saved baseline and returning only new changelog entries, status incidents, OpenAPI operation changes, and Sunset or Deprecation header updates.

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.

Code Mode MCP server for the OVH API. Two tools (search + execute) give LLMs access to all OVH endpoints via sandboxed JavaScript.

An MCP server that automatically discovers API endpoints from any codebase, generates and runs tests, and produces per-role QA audit reports in PDF and XLSX.

A comprehensive suite of HTTP and API testing tools that enables AI agents to perform requests, check endpoint health, and decode JWTs. It also provides utilities for URL parsing and detailed security analysis of HTTP response headers.