"Tools for enabling LLMs to interact with web pages and perform end-to-end testing" matching MCP servers:

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.

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.

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

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.

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.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

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 LLM-driven API testing platform exposed over MCP, enabling declarative test definition and DAG-based execution.

A lightweight, local-first MCP server for executing HTTP requests and managing API collections and environments without cloud dependencies. It enables testing APIs, handling authentication, and importing OpenAPI specifications directly within MCP-compatible workflows.

Automatically converts any OpenAPI specification or Postman Collection into an MCP server, enabling AI assistants like Claude to directly interact with REST APIs without writing any code.

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

A full-stack API automation testing server that parses OpenAPI/Swagger/Postman/HAR specs, generates comprehensive test scenarios and executable code, and provides AI-powered review and auto-fix.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

Turn any GraphQL API into MCP tools. Zero config, zero code. Auto-introspection, flat InputObject schemas for better LLM accuracy, smart truncation, retry logic with exponential backoff.

Converts OpenAPI specifications into MCP services with HTTP header passthrough support. Enables interaction with any OpenAPI-compliant service through natural language by dynamically transforming API documentation into MCP tools.

Automatically converts any OpenAPI specification into an MCP server, exposing all HTTP endpoints as callable tools with support for various authentication methods and request types.