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MCP Mermaid

MCP Mermaid

Remote
github.comMedia & Design646Updated 24w ago

About MCP Mermaid

MCP Mermaid is an MCP server that lets AI clients generate Mermaid diagrams and charts on demand. It suits AI assistants and agents that need visual output, and it validates Mermaid syntax so models can correct errors across several rounds.

Key features

  1. 01Supports all Mermaid features and syntax
  2. 02Configurable backgroundColor and theme styling
  3. 03Exports to base64, svg, mermaid and file formats
  4. 04Provides svg_url and png_url shareable links
  5. 05Validates Mermaid syntax before output

Use cases

  1. 01Letting an AI assistant draw flowcharts or sequence diagrams from chat
  2. 02Having an AI agent save diagrams as PNG files to disk
  3. 03Sharing generated diagrams through public mermaid.ink links

MCP support

This project is an MCP server that exposes diagram generation to MCP clients over stdio, SSE or Streamable HTTP.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://server.smithery.ai/@hustcc/mcp-mermaid/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://server.smithery.ai/@hustcc/mcp-mermaid/mcpAuth required

Tools

Details

From the project README

README image MCP Mermaid MCP Server build npm Version smithery badge npm License Trust Score

Generate README image mermaid diagram and chart with AI MCP dynamically. Also you can use:

  • README image mcp-server-chart to generate chart, graph, map.
  • README image Infographic to generate infographic, such as Timeline, Comparison, List, Process and so on.
  • 🖼️ figure.ling.pub/gallery to browse and share AI-generated diagrams and figures created with mcp-mermaid and other tools.

✨ Features

  • Fully support all features and syntax of Mermaid.

  • Support configuration of backgroundColor and theme, enabling large AI models to output rich style configurations.

  • Support exporting to base64, svg, mermaid, file, and remote-friendly svg_url, png_url formats, with validation for Mermaid to facilitate the model's multi-round output of correct syntax and graphics. Use outputType: "file" to automatically save PNG diagrams to disk for AI agents, or the URL modes to share diagrams through public mermaid.ink links.

mcp-mermaid

🤖 Usage

To use with Desktop APP, such as Claude, VSCode, Cline, Cherry Studio, and so on, add the MCP server config below. On Mac system:

{
  "mcpServers": {
    "mcp-mermaid": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-mermaid"
      ]
    }
  }
}

On Window system:

{
  "mcpServers": {
    "mcp-mermaid": {
      "command": "cmd",
      "args": [
        "/c",
        "npx",
        "-y",
        "mcp-mermaid"
      ]
    }
  }
}

Also, you can use it on aliyun, modelscope, glama.ai, smithery.ai or others with HTTP, SSE Protocol.

Access Points:

  • SSE: http://localhost:3033/sse
  • Streamable: http://localhost:1122/mcp

Available Docker Tags:

  • susuperli/mcp-mermaid:latest - Latest stable version
  • View all available tags at Docker Hub

🚰 Run with SSE or Streamable transport

Option 1: Global Installation

Install the package globally:

npm install -g mcp-mermaid

Run the server with your preferred transport option:

# For SSE transport (default endpoint: /sse)
mcp-mermaid -t sse

# For Streamable transport with custom endpoint
mcp-mermaid -t streamable
Option 2: Local Development

If you're working with the source code locally:

# Clone and setup
git clone https://github.com/hustcc/mcp-mermaid.git
cd mcp-mermaid
npm install
npm run build

# Run with npm scripts
npm run start:sse        # SSE transport on port 3033
npm run start:streamable # Streamable transport on port 1122
Access Points

Then you can access the server at:

  • SSE transport: http://localhost:3033/sse
  • Streamable transport: http://localhost:1122/mcp (local) or http://localhost:3033/mcp (global)

🎮 CLI Options

You can also use the following CLI options when running the MCP server. Command options by run cli with -h.

MCP Mermaid CLI

Options:
  --transport, -t  Specify the transport protocol: "stdio", "sse", or "streamable" (default: "stdio")
  --port, -p       Specify the port for SSE or streamable transport (default: 3033)
  --endpoint, -e   Specify the endpoint for the transport:
                    - For SSE: default is "/sse"
                    - For streamable: default is "/mcp"
  --help, -h       Show this help message

🔨 Development

Install dependencies:

npm install

Build the server:

npm run build
Start the MCP server

Using MCP Inspector (for debugging):

npm run start

Using different transport protocols:

# SSE transport (Server-Sent Events)
npm run start:sse

# Streamable HTTP transport
npm run start:streamable

Direct node commands:

# SSE transport on port 3033
node build/index.js --transport sse --port 3033

# Streamable HTTP transport on port 1122
node build/index.js --transport streamable --port 1122

# STDIO transport (for MCP client integration)
node build/index.js --transport stdio

🐳 Docker Usage

Run MCP Mermaid with Docker:

# Pull the image
docker pull susuperli/mcp-mermaid:latest

# Run with SSE transport (default)
docker run -p 3033:3033 susuperli/mcp-mermaid:latest --transport sse

# Run with streamable transport
docker run -p 1122:1122 susuperli/mcp-mermaid:latest --transport streamable --port 1122

📄 License

MIT@hustcc.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.