"A service for managing a to-do list and task reminders" matching MCP servers:

Provides tools to communicate with a service dependency API, enabling users to query and interact with service relationship data and dependency mappings.

A unified HTTP/HTTPS service that exposes Model Context Protocol (MCP) functionality over HTTP endpoints, allowing clients to list available tools and call them through a standardized API.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

Enables generation of API and integration documentation, English/French translation, and quality linting for technical docs.

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.

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.

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.

Enables AI agents to test WCF/SOAP and REST services directly, with WSDL discovery, authenticated calls, and deterministic assertions. Supports YAML multi-step scenarios with variable extraction, JSONPath/JSON Schema checks, and CI runs without spawning PowerShell or curl.

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.

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.

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.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

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

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.

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.

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