@processon/mcp-server-processon-node
# @processon/mcp-server-processon-node
> 🧠 基于 Node.js + TypeScript 实现的 [ProcessOn](https://www.processon.com) MCP Server,支持从 Markdown 内容自动生成思维导图。
## 📦 项目地址
- GitHub: [https://github.com/liqi888/mcp-server-processon-node](https://github.com/liqi888/mcp-server-processon-node)
- npm: [https://www.npmjs.com/package/@processon/mcp-server-processon-node](https://www.npmjs.com/package/@processon/mcp-server-processon-node)
## ⚙️ 环境变量配置
- 服务通过环境变量读取 ProcessOn 配置信息:
| 变量名 | 是否必须 | 说明 |
|----------------------|----------|--------|
| `PROCESSON_API_KEY` | ✅ 是 | 你的 ProcessOn API 密钥(可在 [www.processon.com](https://www.processon.com/setting) 账户中心 获取) |
| `BASE_URL` | ❌ 否 | 自定义 API 地址(默认使用官方地址) |
- 在项目根目录下创建 `.env` 文件,或通过环境变量方式传入以下配置:
```env
# 必填,用于调用 ProcessOn 接口
PROCESSON_API_KEY=你的 API Key
# 可选,自定义 ProcessOn 服务地址
BASE_URL=https://www.processon.com
```
---
## 🧠 支持的工具能力(Tools)
### 1. check
- **作用**:检查当前配置的 `PROCESSON_API_KEY` 是否生效。
- **输入参数**:无
- **返回**:当前 `API_BASE` 和 `API_KEY` 的拼接值
---
### 2. createProcessOnMind
- **作用**:根据 Markdown 内容生成思维导图,并返回可视化链接。
- **输入参数**:
- `title`: string,思维导图文件名
- `content`: string,Markdown 内容,支持二级以上标题和列表格式
- **输出结果**:成功返回 `https://www.processon.com/mindmap/xxxxxx` 的可访问地址
---
## 🧰 本地开发与调试(项目开发或维护者使用)
### 1. 将GitHub项目下载到本地
```
mcp-server-processon-node/
├── src/ # 源代码目录(TypeScript 源文件)
│ └── index.ts # 服务主入口,定义 MCP 方法、注册 Handler 等
├── chatmcp.yaml # MCP 配置文件,用于描述服务元信息、能力、参数
├── package.json # NPM 项目配置文件,定义依赖、脚本、元数据
├── package-lock.json # 锁定依赖版本,确保构建一致性
├── tsconfig.json # TypeScript 编译配置文件
└── README.md # 项目说明文档(功能简介、安装、用法等)
```
### 2. 终端进入到项目根目录执行以下命令
```bash
# 安装依赖
npm install
# 本地开发时持续监听构建
npm run watch
# 构建项目
npm run build
# 使用 npm link 注册本地命令
npm link
```
### 3. Cherry Studio 本地配置示例:
- **说明**:启动成功后即可在右侧工具栏中看到 `check` 和 `createProcessOnMind` 两个工具接口。
```json
"processon_mind_local": {
"name": "ProcessOn_CreateMind",
"type": "stdio",
"description": "ProcessOn创建思维导图",
"isActive": true,
"registryUrl": "",
"command": "npx",
"args": [
"mcp-server-processon-node"
],
"env": {
"PROCESSON_API_KEY": "{YOU PROCESSON_API_KEY}"
}
}
```
### 4. 打包发布到 npm
```bash
# 登录
npm login
# 发布
npm publish --access public
```
---
## 🧩 Cherry Studio 正式包配置示例:
| 字段 | 值 |
| -- | ------------------------------ |
| 类型 | 标准输入/输出(stdio) |
| 命令 | npx |
| 参数 | @processon/mcp-server-processon-node@latest |
|环境变量|PROCESSON_API_KEY={YOU PROCESSON_API_KEY}|
**说明**:
1. @latest 可以替换成具体的版本号(例如 @1.0.9)
2. 你的 ProcessOn API 密钥可在 [www.processon.com](https://www.processon.com/setting) 账户中心获取
```bash
# 底层实际执行命令
npx @processon/mcp-server-processon-node@latest
```
3. 启动成功后即可在右侧工具栏中看到 `check` 和 `createProcessOnMind` 两个工具接口。
4. JSON配置示例
```json
"processon_mind_online": {
"name": "ProcessOn_CreateMind",
"type": "stdio",
"description": "ProcessOn创建思维导图",
"isActive": true,
"registryUrl": "",
"command": "npx",
"args": [
"@processon/mcp-server-processon-node@latest"
],
"env": {
"PROCESSON_API_KEY": "{YOU PROCESSON_API_KEY}"
}
}
```
---
## 🚀 安装使用
### 方式一:通过 npx 启动(推荐)
```bash
npx @processon/mcp-server-processon-node@latest
```
> ⚠️ 若执行卡在 `dotenv` 提示不动,建议手动指定版本并添加环境变量 `.env` 文件。
---
### 方式二:全局安装后使用
```bash
npm install -g @processon/mcp-server-processon-node
# 启动服务
mcp-server-processon-node
```
---
### 方式三:作为依赖引入到 Node 项目中
```bash
npm install @processon/mcp-server-processon-node
```
---
## 📄 License
MIT © 2025 [琪天大圣](https://github.com/liqi888/mcp-server-processon-node)TDQS
Scored across 2 tools
The two tools, 'check' and 'createProcessOnMind', serve clearly different purposes: one checks the API key configuration, the other creates a mind map from markdown. There is no overlap or ambiguity.
Naming style is inconsistent: 'check' is a simple lowercase verb, while 'createProcessOnMind' uses camelCase. With only two tools, the lack of a consistent pattern is noticeable.
Having only two tools seems too few for a server dedicated to ProcessOn functionality. A typical mind map service would include at least creation, listing, and perhaps deletion, making this feel incomplete and minimal.
The tool surface is severely incomplete for mind map management. Only creation is supported; there are no tools for listing, viewing, updating, or deleting mind maps, which limits the agent's ability to perform a full workflow.