mermaid-mcp

mermaid-mcp

Renders Mermaid diagram markup to PNG images using Puppeteer/Chromium. Enables AI-generated diagrams to be previewed inline and saved to disk.

Category
访问服务器

README

mermaid-mcp

An MCP server that renders Mermaid diagram markup to PNG images, using @mermaid-js/mermaid-cli (Puppeteer/Chromium) under the hood.

Give it AI-generated Mermaid — flowcharts, sequence, class, ER, gantt, state diagrams — and get back a rendered image, returned inline so the host can preview it and/or written to a file on disk.

Tool

render_mermaid

Parameter Type Required Description
diagram string yes Mermaid diagram source, e.g. graph TD; A-->B;
outputPath string no Absolute path ending in .png to also save the image to. Omit to only return inline.
theme enum no default | dark | forest | neutral (default default)
backgroundColor string no e.g. white, transparent, #ffffff (default white)
width number no Output width in pixels
height number no Output height in pixels
scale number no Device scale factor; higher = sharper/larger PNG (default 1)

Returns a short text summary plus the PNG as inline MCP image content. When outputPath is supplied, the file is written there and the path is included in the summary.

Install & build

npm install
npm run build

Browser requirement

Mermaid renders inside a real browser (it needs a DOM for layout), so Google Chrome / Chromium is required. Puppeteer resolves it, in this order:

  1. PUPPETEER_EXECUTABLE_PATH — an explicit Chrome/Chromium binary you point it at.
  2. Puppeteer's bundled Chromium — downloaded by @mermaid-js/mermaid-cli during npm install.
  3. A system-installed Google Chrome — used as a fallback (channel: "chrome") if the bundled browser can't be launched.

If none can be launched, the tool returns an actionable error: install Chrome, run npx puppeteer browsers install chrome, or set PUPPETEER_EXECUTABLE_PATH.

If Puppeteer's automatic Chromium download is blocked (a locked-down network, or — on some Windows machines — a stalled extraction), just install Google Chrome and the renderer falls back to it.

Test

npm test

Integration tests using Node's built-in test runner (node:test). They exercise the renderer (input validation, inline render, render-to-file) and a full MCP stdio round-trip (spawn the server, list tools, call render_mermaid). The render tests launch headless Chromium, so they need the Chromium install above and take a few seconds each.

Configure in an MCP client

After npm run build, point your MCP client at the built entry over stdio.

Claude Code

# From a local build:
claude mcp add mermaid -- node /absolute/path/to/mermaid-mcp/dist/index.js

# Or from the published package:
claude mcp add mermaid -- npx -y @volare-consulting/mermaid-mcp

Claude Desktop / generic mcpServers config

{
  "mcpServers": {
    "mermaid": {
      "command": "node",
      "args": ["/absolute/path/to/mermaid-mcp/dist/index.js"]
    }
  }
}

Development

npm run dev     # run the server from TypeScript source via tsx

Releasing

Published to the public npm registry as @volare-consulting/mermaid-mcp via a tag-driven GitHub Actions release (.github/workflows/publish.yml), which calls the org's shared publish-npm-public reusable workflow.

  1. Bump version in package.json on a PR and merge to main.

  2. Tag the merge commit and push the tag:

    git tag v0.1.0 && git push origin v0.1.0
    

The tag must equal the package.json version or the job fails. Pushing a v* tag builds and publishes the package (tests are skipped — they need headless Chromium the publish runner doesn't provide). Authentication uses the org-level NPM_TOKEN secret.

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选