"MCP servers for curated context in Cursor IDE to plan, debug, and iterate on features" 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.

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

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.

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.

A configurable MCP server that intelligently routes natural language queries to the appropriate microservice endpoint based on user-defined service configurations.

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.

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.

A simple MCP server that can enable MCP clients to query Bluesky instances.

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.

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.

Enables AI agents to safely inspect a PortalV4 project's real structure, database schema, and Git status, while enforcing backend architecture rules, automating API documentation, and generating test templates without modifying repositories.

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.

Integrates XAPIHub API services with the Cursor IDE to enable user authentication, real-time data fetching, and connection diagnostics. It allows developers to interact with their XAPIHub organization and manage user details directly through natural language commands.

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.

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

A proxy server that bridges AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools, enabling seamless interaction without custom integration code.

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.

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.

Free JSON Schema validation, JSON to TypeScript, CSV to JSON, JSON repair and JSON to CSV for AI agents. Hosted MCP plus local STDIO. Connect once with a scoped key; enforce tool allowlists and quotas, inspect request IDs. Runnable repair → validate → CSV workflow. Bounded OpenAPI and webhook checks. No LLM calls or payments. Setup: invokeport.com/agents.

Connects AI agents to Postman workspaces, collections, API specifications, and environments for API testing, management, and client code generation.

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

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.

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.

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.