"Command Line Interface (CLI) for CMD" matching MCP servers:

This server automatically validates consistency between AI-generated frontend and backend code by enforcing OpenAPI 3.0 specifications. It injects smart constraints into AI prompts to ensure that generated data structures and API calls remain synchronized across the entire stack.

A Model Context Protocol server that allows AI development tools like Cursor and Claude Desktop to retrieve detailed YAPI interface information by interface ID.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

An MCP server for the YAPI interface management platform that enables users to manage projects, categories, and API interfaces. It supports querying project details, listing interfaces, and creating or modifying API documentation through natural language.

MCP server for Akamai APIs. 198 tools covering Property Manager, Edge DNS, CPS, WAF, and reporting. Built with TypeScript, featuring modular architecture, comprehensive testing, and multi-account support. Make Akamai accessible to AI assistants.

Free x402 endpoint checker plus paid report and metadata tools. Remote MCP server for agents. Written by AI named Nock, not a human.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

MCP server for mockzilla. Lets coding agents (Claude Desktop, Cursor, etc.) install the mockzilla CLI, stand up API mocks from an OpenAPI spec or a single endpoint, and — with an account — deploy hosted mocks on mockzilla.org.

A local MCP server that lets clients discover, inspect, and execute Bruno OpenCollection API collections, while delegating request execution, authentication, scripting, assertions, and environment resolution to the Bruno CLI.

CLIRank - API discovery for AI agents. APIs scored on CLI relevance: auth method, JSON responses, headless operation, pricing transparency. Search by capability, compare alternatives, read agent-contributed docs. 6 MCP tools for discovery, comparison, and documentation. Agents contribute observations back - crowdsourced API docs by machines, for machines.

A Model Context Protocol (MCP) server for authenticated REST APIs. Drop it into any project, point it at your API, and let AI agents call endpoints — with auto-login, 2FA support, Swagger spec fetch, and fuzzy endpoint search — all without writing a single line of auth code.

A reusable MCP server for QA automation testing that enables running tests across web apps, APIs, CLI tools, and more directly from Claude Desktop.

Turn any OpenAPI spec into MCP tools for Claude — instantly. Point mcp-openapi at any OpenAPI 3.x spec and Claude can call every endpoint through natural language. No custom integration code. No manual tool definitions. One line of config.

Enables searching YApi interfaces by keyword and retrieving detailed interface schemas, including request/response, for project-level tokens.

Integrates Bruno CLI for API testing, enabling users to run API requests and collections, manage environments, generate test reports (JSON/JUnit/HTML), and validate collection structures through natural language commands.

Enables AI agents to create, edit, read, and run Bruno API collections (both .bru and .yml formats) with byte-parity to Bruno's own reader, without requiring the Bruno CLI.

A server that enables management of ApiPost API documentation and team collaboration through the Model Context Protocol, supporting complete interface management directly from compatible editors.

Enables AI assistants to access and search RAP2 API documentation, allowing users to query interface details, search APIs by keywords, and retrieve repository interfaces through natural language.