AI导哈

MCP服务器生成工具

mcpkit 是一款面向开发者的开源命令行工具，核心功能是根据 OpenAPI 规范、SQLite 数据库或 YAML 描述快速生成可直接运行的 MCP 服务器，适用于将现有 API 与数据接入 AI 助手等场景。

  • by BenihDev
  • TypeScript
  • 本地部署
  • 更新于
在 GitHub 查看 fanioz/mcpkit

使用说明

mcpkit

Generate ready-to-use MCP servers from OpenAPI specs, databases, or YAML descriptions.

mcpkit is a free, open-source CLI tool by BenihKode — a solo developer studio that ships small, focused dev tools. Full docs, examples, and the rest of the toolset live at benihkode.web.id.

Model Context Protocol is the standard for connecting AI assistants to your tools and data. mcpkit gets you from zero to a working MCP server in seconds.

Install

npx @fanioz/mcpkit

Usage

Create a blank MCP server

npx @fanioz/mcpkit init
# or with flags:
npx @fanioz/mcpkit init --name my-server --description "My custom MCP server"

Generate from an OpenAPI spec

Turns every endpoint into an MCP tool. Supports OpenAPI 3.x and Swagger 2.x.

npx @fanioz/mcpkit from openapi.yaml
npx @fanioz/mcpkit from openapi.yaml --name petstore-mcp
npx @fanioz/mcpkit from openapi.yaml --name my-api -o ./output-dir

Example — generate from a public API spec:

npx @fanioz/mcpkit from https://api.example.com/openapi.yaml --name example-mcp
cd example-mcp
npm install
npm run dev

What it does:

Given petstore.yaml:

openapi: 3.0.0
info: { title: Petstore API, version: "1.0.0" }
servers: [{ url: https://petstore.example.com/api }]
paths:
  /pets/{petId}:
    get:
      operationId: getPetById
      summary: Get a pet by ID
      parameters:
        - name: petId
          in: path
          required: true
          schema: { type: string }
      responses:
        "200": { description: The requested pet }
  /pets:
    post:
      operationId: createPet
      summary: Add a new pet
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required: [name]
              properties:
                name: { type: string }
                tag: { type: string }
      responses:
        "201": { description: The created pet }

mcpkit generates a project whose src/index.ts contains one MCP tool per endpoint:

server.tool(
  "getpetbyid",
  "Get a pet by ID",
  { petId: z.string() },
  async ({ petId }) => {
    const url = `https://petstore.example.com/api/pets/${encodeURIComponent(petId)}`;
    // fetch + return the JSON response as the tool result
  }
);

server.tool(
  "createpet",
  "Add a new pet",
  { name: z.string(), tag: z.string().optional() },
  async ({ name, tag }) => {
    // POST with body: JSON.stringify({ name, tag })
  }
);

Register it in your AI assistant and you can ask "get pet number 42" and it calls your real API.

Generate from a SQLite database

Creates read-only query tools for every table in your database.

npx @fanioz/mcpkit from sqlite:///path/to/your.db
npx @fanioz/mcpkit from sqlite:///path/to/your.db --name my-db-mcp

For every table, the generated server exposes a read-only query tool:

server.tool(
  "list_users",
  "List rows from the users table",
  {
    limit: z.number().optional().describe("Max rows to return (default 100)"),
    where: z.string().optional().describe("SQL WHERE clause (use with caution)"),
  },
  async ({ limit = 100, where }) => {
    // SELECT * FROM users [WHERE ...] LIMIT ?
  }
);

The database is copied into the generated project as data.db and opened read-only.

Generate from a YAML description

Define your MCP tools in a simple YAML file:

# mcp.yml
name: my-tools
version: "1.0.0"
description: My custom MCP server
tools:
  - name: search
    description: Search for items
    parameters:
      - name: query
        type: string
        description: Search query
        required: true
      - name: limit
        type: string
        description: Max results
        required: false

npx @fanioz/mcpkit from mcp.yml

Generated project structure

Every command outputs a ready-to-run TypeScript project:

my-mcp-server/
  package.json
  tsconfig.json
  src/
    index.ts        # MCP server with your tools
  .gitignore

cd my-mcp-server
npm install
npm run dev        # Start the MCP server

Use with AI assistants

Add your generated MCP server to your AI assistant's config:

Claude Code (~/.claude/settings.json):

{
  "mcpServers": {
    "my-server": {
      "command": "node",
      "args": ["/path/to/my-mcp-server/src/index.ts"]
    }
  }
}

Cursor / Windsurf — add to your MCP settings.

YAML spec reference

name: server-name          # Required: kebab-case server name
version: "1.0.0"           # Optional: version string
description: My server     # Optional: description
tools:
  - name: tool_name        # Required: tool identifier
    description: What it does  # Required
    parameters:
      - name: param_name   # Required: parameter name
        type: string       # Required: parameter type
        description: Help text  # Optional
        required: true     # Optional: default false

Links

License

MIT

Part of the BenihKode developer toolset.

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