MCP-OpenAPI Server는 AI Agent를 활성화하여 기존의 API 엔드포인트와 Model Context Protocol (MCP)를 통해 검색하고 상호 작용할 수 있는 교량입니다. MCP 도구로 OpenAPI-defined 서비스를 이용하여 적절한 타이핑, 인증 및 선택적 엔드포인트 노출을 통해 사용자 정의 도구 개발을 요구하지 않고 클라우드 기반 AI 에이전트 및 외부 서비스 간의 통합을 단순화합니다.

많은 MCP 구현은 로컬 통합 및 명령 줄 도구에 의존하지만, 이 프로젝트는 SSE 운송에 초점을 맞추고 멀티 터미널 서버 측 아키텍처를 가능하게합니다.

이 누구를 위해?

• API 공급자: API를 재건하거나 사용자 정의 MCP 도구를 만들지 않고 AI 에이전트에 OpenAPI 서비스를 쉽게 노출. 플랫폼과 AI 통합을 가능하게 하는 SaaS 기업을 위한 완벽한.

• AI 에이전트 개발자: 서버 측 에이전트를 여러 외부 서비스에 연결하여 제대로 입력된 인수. Zendesk, Stripe 및 기타 API와 같은 시스템과 원활하게 상호 작용할 수 있는 건물 조수에 이상적입니다.

MCP-OpenAPI Server

MCP-OpenAPI Server is a bridge that enables AI agents to discover and interact with your existing API endpoints through the Model Context Protocol (MCP). By exposing OpenAPI-defined services as MCP tools with proper typing, authentication, and selective endpoint exposure, it simplifies integration between cloud-based AI agents and external services without requiring custom tool development.

While many MCP implementations rely on stdiofor local integrations and command-line tools, this project focuses on SSE transport to enable a multi-tenant server-side architecture.

Who is This For?

• API Providers: Easily expose your OpenAPI services to AI agents without rebuilding APIs or creating custom MCP tools. Perfect for SaaS companies wanting to enable AI integration with their platform.

• AI Agent Developers: Connect your server-side agents to multiple external services with properly typed arguments. Ideal for building assistants that can seamlessly interact with systems like Zendesk, Stripe, and other APIs.

• Enterprise Integration Teams: Create standardized access patterns for AI agents to interact with your internal systems while maintaining proper authentication and permissions.

• Prototype Developers: Quickly test AI-API interactions before investing in a dedicated MCP implementation, helping identify improvements to your API structure and documentation.

Key Features

• SSE Transport: This server leverages the SSE transport for MCP (rather than Stdio) so it works well for multiple agent clients.
  • Each OpenAPI server is available at a separate route //sse (e.g., https://my-mcp-server/stripe/sse).
• Selective Route Exposure: Expose only the routes/tools you want for your agents to be aware of, using a regex on the route.
• Authentication Forwarding: Share the same MCP tools across multiple users by forwarding the appropriate authorization headers and/or query parameters.
• Type Safety: Tools are generated with typed arguments based on the OpenAPI schema.
  • JSON bodies and parameters are converted appropriately with supported for nested objects and more complex schemas.

Running

Start the Server

Define your servers in servers.yaml following the structure in servers.yaml.example and:

servers:
  - namespace: stripe
    # Forward the Authorization header to the Stripe API
    forward_headers:
      - Authorization
    name: Stripe API
    url: https://raw.githubusercontent.com/stripe/openapi/refs/heads/master/openapi/spec3.yaml
    base_url: https://api.stripe.com
    # Select which API paths to expose over MCP. Each matching path will become a tool with arguments
    # from the query parameters or the JSON body.
    # For example, we're only exposing the endpoints to GET/POST a customer.
    paths:
      - /v1/customers$

  - namespace: zendesk