How does AI access the API documentation data?
AI reads all API documentation data from the entire Apifox project through the MCP protocol, with data cached locally on your computer.
@apifox
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"API 文档": {
"command": "npx",
"args": [
"-y",
"apifox-mcp-server@latest",
"--project-id=<project-id>"
],
"env": {
"APIFOX_ACCESS_TOKEN": "<access-token>"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
Apifox MCP Server provides Apifox project API documentation as data to AI programming IDE tools like Cursor, enabling AI to directly access project API documentation.
Install Node.js 18+, generate an Apifox access token, obtain a project ID, then add the MCP configuration JSON to your IDE's MCP configuration file (e.g., ~/.cursor/mcp.json or Cline's MCP Server settings).
/users)AI reads all API documentation data from the entire Apifox project through the MCP protocol, with data cached locally on your computer.
Tell AI to refresh the API documentation data, otherwise AI may read outdated cached data.
Apifox MCP Server supports Cursor and VSCode with the Cline plugin, both of which support the MCP protocol.
Besides Apifox projects, the server also supports reading Swagger/OAS files directly via the `--oas` parameter (URL or local file path).
Name the MCP Server with "API文档" in its name for AI to recognize its purpose, avoid leaking access tokens in shared repositories, and add `--apifox-api-base-url` for on-premises deployment users.
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