mcp-swagger-schema
An MCP server that allows users to query and retrieve request and response JSON schemas directly from Swagger/OpenAPI specifications. It supports automatic reference resolution and path parameter matching to help AI models interact with API interfaces.
README
mcp-swagger-schema
一个 MCP (Model Context Protocol) 服务器,用于查询 Swagger 规范中的接口 schema。
功能
- 根据 API 路径获取请求和响应的 JSON Schema
- 自动解析
$ref引用 - 支持路径参数匹配(如
/api/users/{id}) - 内置缓存机制
快速开始
第一步:找到你的 Swagger JSON 地址
你需要先获取项目的 Swagger/OpenAPI 规范地址,通常是类似这样的 URL:
https://your-api.com/v3/api-docs
第二步:配置 MCP 服务器
在你的 MCP 配置文件中(通常是 .mcp/config.json 或类似的配置),添加如下配置:
{
"mcpServers": {
"swagger-schema": {
"command": "npx",
"args": ["-y", "mcp-swagger-schema"],
"env": {
"SWAGGER_SPEC_URL": "替换成你的swagger地址"
}
}
}
}
⚠️ 常见问题:找不到 npx 命令
如果启动失败,提示找不到 npx,按以下步骤解决:
步骤 1:打开终端,运行以下命令
which npx
你会看到类似这样的输出:
/Users/你的用户名/.nvm/versions/node/v20.0.0/bin/npx
步骤 2:复制 bin 目录路径
把上面输出的路径,去掉最后的 /npx,得到 bin 目录:
/Users/你的用户名/.nvm/versions/node/v20.0.0/bin
步骤 3:修改配置,添加 PATH
{
"mcpServers": {
"swagger-schema": {
"command": "npx",
"args": ["-y", "mcp-swagger-schema"],
"env": {
"SWAGGER_SPEC_URL": "替换成你的swagger地址",
"PATH": "步骤2得到的路径:/usr/bin:/bin"
}
}
}
}
例如:
{
"mcpServers": {
"swagger-schema": {
"command": "npx",
"args": ["-y", "mcp-swagger-schema"],
"env": {
"SWAGGER_SPEC_URL": "https://api.example.com/swagger.json",
"PATH": "/Users/zhangsan/.nvm/versions/node/v20.0.0/bin:/usr/bin:/bin"
}
}
}
}
使用方法
配置完成后,在对话中直接说:
获取 /api/users 接口的 schema
AI 会调用工具返回该接口的请求参数和响应结构。
工具参数说明
| 参数 | 必填 | 说明 |
|---|---|---|
path |
✅ | 接口路径,如 /api/users |
method |
❌ | HTTP 方法(get/post/put/delete),不填会自动选择 |
返回示例
{
"found": true,
"path": "/api/users",
"method": "post",
"summary": "创建用户",
"request": {
"body": {
"type": "object",
"properties": {
"name": { "type": "string" },
"email": { "type": "string" }
}
}
},
"response": {
"type": "object",
"properties": {
"id": { "type": "integer" },
"name": { "type": "string" }
}
}
}
环境变量
| 变量名 | 必填 | 说明 |
|---|---|---|
SWAGGER_SPEC_URL |
✅ | Swagger/OpenAPI JSON 规范的 URL |
SWAGGER_CACHE_TTL_MS |
❌ | 缓存过期时间(毫秒),默认 60000 |
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.