"openapi" matching MCP servers:

Converts any OpenAPI v3 spec into an MCP server with typed tools, resources, and prompts, enabling AI agents to call any REST API via natural language.

A tool that accelerates MCP protocol adoption by automatically generating MCP-compatible server components from OpenAPI specifications, enabling seamless integration with existing services as a sidecar.

A command-line tool that transforms any OpenAPI service into a Model Context Protocol (MCP) server, enabling seamless integration with AI agents and tools that support the MCP specification.

🤖 Taskade MCP · Official MCP server and OpenAPI to MCP codegen. Build AI agent tools from any OpenAPI API and connect to Claude, Cursor, and more.

Projects an Agent Surface (deterministic call graph) for any OpenAPI, enabling LLM agents to make correct, chain-of-calls interactions without guessing.

An autonomous Go MCP server that dynamically imports OpenAPI, GraphQL, and AsyncAPI specs and exposes them as tools to agents with self-learning and auto-documentation.

Enables building agent-ready APIs that expose tools as both HTTP and MCP endpoints from a single server definition, with automatic OpenAPI, discovery docs, and interactive API reference.

A dynamic proxy that converts OpenAPI Specification (OAS) endpoints into Message Communication Protocol (MCP) tools, allowing AI agents to use existing REST APIs as if they were native MCP tools without manual implementation.

Enables autonomous frontend and backend AI agents to asynchronously coordinate development by registering and discovering OpenAPI-compatible route contracts, tracking integration issues, and managing route groups for efficient LLM context.

One command to turn any codebase into an MCP server. Not just REST APIs. Not just OpenAPI specs.

A secure tool-execution plane for agentic AI that enforces JWT authentication, rate limiting, prompt-injection inspection, and audit logging, while ingesting downstream OpenAPI endpoints as MCP tools.

Enables connecting any number of OpenAPI, GraphQL, and MCP servers to MCP clients through a single local endpoint, with a web UI for management, unified tool exposure, and policy controls.

Enables building and running MCP servers from a single executable, with shared daemons, concurrency controls, retries, caching, security, and OpenAPI integration.

Enables autonomous agents to turn high-level project goals into structured user stories, verifiable Gherkin acceptance criteria, edge cases, and OpenAPI-compatible API contract skeletons through MCP tools.

An MCP Server that enables interaction with the Obono RKSV API, automatically generated using AG2's MCP builder to provide a standardized way to access the functionality defined in the OpenAPI specification.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

Provides a JSON-RPC MCP server that exposes policy-governed agent tools, including paid tools, tool muxing, and OpenAPI-to-MCP conversion, enabling agents to discover, coordinate, and execute tasks within the ProtoOS ecosystem.

Lets an AI coding agent offload low-complexity, monotonous tasks to a cheap local or OpenAI-compatible model that runs its own server-side tool loop for reading, searching, and staging file writes, so large file contents and intermediate steps never enter the caller's context. Also provides summaries, extraction, classification, bulk file mapping, staged-diff review, model management, and session token-savings reporting.

67 tools generated from the same OpenAPI spec as our SDKs — CI fails on drift, so REST and MCP never disagree. Underneath: a deterministic field operations scheduling engine — skills, territories, live availability, sub-3-second cascade rescheduling — drivable end-to-end from Claude or ChatGPT. Schedule changes preview before they commit; LLMs never inside the math.

Enables interaction with OpenAI's Chat Completion and Assistants APIs, supporting assistant management, file operations, and direct queries to GPT models through standardized MCP tools.