"Methods to Extract Data from Files" matching MCP servers:

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

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

Generates standalone, human-readable MCP servers from RAML 1.0 or OpenAPI 3.x specs, exposing one tool per resource and method that makes real HTTP calls. It understands Mule/Anypoint auth patterns such as Client ID enforcement and OAuth2, wiring the expected credentials from environment variables at call time.

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

Enables MCP clients to expose selected operations from local OpenAPI 3.0/3.1 documents as tools, with stdio serving or generated standalone server projects and read-only defaults.

Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

MCP server that fetches API responses and generates ready-to-use model/POJO classes in your configured language, with built-in login/refresh token handling.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

A bridge that enables any LLM to access and interact with documented REST APIs through the Model Context Protocol (MCP).

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Converts any OpenAPI 3.x spec into a live MCP server, making every endpoint a validated tool that AI agents can call without writing glue code.

An MCP server that exposes an OpenAPI interface matching tool via Streamable HTTP Transport, allowing clients to match JSON against an OpenAPI specification.

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

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

Provides a testable gateway path for running a local MCP-style server in hosted-like conditions, with tenant-isolated reads, approval-denied writes, deterministic failures, and smoke-test verification.

An MCP server that mocks payments, third-party API responses, and test data to enable QA flows for donation, checkout, SIP, and subscription pages without depending on a live gateway.