"Using AI to control and access data from Home Assistant and smart home devices" matching MCP servers:

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

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 LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

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

Enables browser automation and API testing for AI agents using Playwright and Chrome DevTools Protocol, with numbered element references, Set-of-Mark screenshots, flow recording/replay, element memory, captcha handoff, and HTTP API test suites.

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

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.

This MCP server enables interaction with Google's Verified Access API, allowing users to verify the security posture of Chrome OS and Chrome Browser devices through natural language commands.

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.

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.

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 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.

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.