mcpify

mcpify

Turn any REST API into an MCP server in one command. Point mcpify at an OpenAPI spec and every endpoint becomes a tool your AI agent (Claude, Cursor, Windsurf) can call — zero glue code, always in sync with the spec.

Category
访问服务器

README

mcpify

Turn any REST API into an MCP server in one command. Point mcpify at an OpenAPI spec and every endpoint becomes a tool your AI agent (Claude, Cursor, Windsurf, …) can call — no glue code, no per-endpoint wrappers.

mcpify https://api.example.com/openapi.json

That's it. Every operation in the spec is now a live MCP tool.


Why

MCP is how AI agents call real tools. But wiring an existing API into MCP means hand-writing a tool wrapper for every endpoint — tedious and stale the moment the API changes. Almost every API already publishes an OpenAPI spec. mcpify reads that spec and generates the whole MCP server at runtime, so:

  • Zero per-endpoint code — N endpoints → N tools, automatically.
  • Always in sync — regenerate from the spec; no wrappers to maintain.
  • Auth-aware — pass an API key / bearer token once, applied to every call.

Install

pipx install mcpify-cli      # or: uvx mcpify-cli ...

Use

Preview the tools a spec produces (no server):

mcpify --list examples/petstore-mini.yaml

Run it as an MCP server (stdio):

mcpify https://petstore3.swagger.io/api/v3/openapi.json
mcpify ./openapi.yaml --base-url https://staging.internal.api
mcpify ./openapi.yaml --auth "Authorization: Bearer $TOKEN"   # or set MCPIFY_AUTH

Plug it into Claude

Add to your MCP client config (Claude Desktop / Claude Code mcp.json):

{
  "mcpServers": {
    "petstore": {
      "command": "mcpify",
      "args": ["https://petstore3.swagger.io/api/v3/openapi.json"]
    }
  }
}

Restart the client and ask: "list the available pets" — Claude calls the API directly.

How it works

  1. Load the OpenAPI 3.x document (URL or file, JSON or YAML).
  2. Walk every path/method into an Operation with a generated JSON input schema.
  3. Serve them over MCP; each tool call is mapped to a live HTTP request (path, query, header params and JSON bodies all handled) and the response is returned to the agent.

Supported

  • OpenAPI 3.x, JSON or YAML, from a URL or local file
  • GET / POST / PUT / PATCH / DELETE
  • Path, query, and header parameters; JSON request bodies
  • A single global auth header (API key or bearer token)

Roadmap

  • Per-operation filtering (--only, --tag) to expose a subset of a large API
  • $ref resolution for fully-expanded body schemas
  • Swagger 2.0 specs
  • SSE / HTTP transport in addition to stdio

PRs welcome.

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选