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@processon/mcp-server-processon-node

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@processon/mcp-server-processon-node

🧠 基于 Node.js + TypeScript 实现的 ProcessOn MCP Server，支持从 Markdown 内容自动生成思维导图。

📦 项目地址

Related MCP server: Mind Map MCP Server

⚙️ 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 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：

# 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

# 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。

"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


# 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 账户中心获取

# 底层实际执行命令

npx @processon/mcp-server-processon-node@latest

  1. 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。

  2. JSON配置示例


"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）

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

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

npm install @processon/mcp-server-processon-node

📄 License

MIT © 2025 琪天大圣

Available Tools

2 tools
checkA

查询用户当前配置apiKey，版本1.0.10

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions 'query' implying read-only, but lacks disclosure of behavioral traits like authentication requirements, error cases, or what happens if no apiKey is configured.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. It is front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description adequately covers the tool's purpose for a simple parameterless query. However, it omits return format and error scenarios, leaving minor gaps in completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the description need not add meaning beyond schema. Schema coverage is 100%, meeting the baseline for this case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it queries the user's current configured apiKey. The verb 'query' and resource 'apiKey' are specific, and it distinguishes from the sibling tool 'createProcessOnMind' which is for creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives. It only describes the action, leaving the agent to infer usage context from the tool name and sibling context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

createProcessOnMindB

创建思维导图。根据markdown内容创建思维导图并返回ProcessOn文件链接。

ParametersJSON Schema
NameRequiredDescriptionDefault
titleYes文件名称
contentYesmarkdown形式的内容

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description does not disclose behavioral traits such as side effects, permissions, rate limits, or data persistence. It only states that it creates and returns a link, which is minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences, concise and front-loaded. No extraneous information, though the second sentence partly repeats the first. Efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description mentions the return value (ProcessOn file link), which is good. However, it lacks details on error handling, size limits, or other constraints. It is minimally complete for a simple creation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters ('文件名称' and 'markdown形式的内容'). The description reiterates that content is in markdown form, adding minimal extra meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a mind map from markdown content and returns a ProcessOn file link. The verb 'create' and resource 'mind map' are specific, and the tool is easily distinguishable from the only sibling 'check'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The sibling 'check' is not explained, and there is no mention of prerequisites or context for using this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv1.0.10
    • First observedcheck
    • First observedcreateProcessOnMind
Install Server
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TDQS

B3.3/5.0
Disambiguation5/5

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 Consistency3/5

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.

Tool Count2/5

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.

Completeness2/5

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.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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Related MCP Connectors

Related MCP Servers

  • Markmap MCP Server

    jiushan-test
    A
    license
    Not graded
    quality
    D
    maintenance
    Enables conversion of plain text descriptions and Markdown content into interactive mind maps using AI. Automatically uploads generated mind maps to Aliyun OSS and provides online access links.
    34
    1
    MIT

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