ai.smithery/hustcc-mcp-mermaid

MCP Mermaid

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

• mcp-server-chart to generate chart, graph, map.
• 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.

🤖 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.