Peng Shawn Mermaid MCP Server

Overview

The Mermaid MCP Server bridges the gap between text‑based diagram specifications and visual representations by converting Mermaid markdown into high‑quality PNG images. For developers building AI assistants that need to generate or manipulate diagrams on the fly, this server removes the need to embed a full browser stack in every client or to rely on external rendering services. Instead, the server runs as a lightweight MCP endpoint that accepts Mermaid code, renders it using Puppeteer, and returns a ready‑to‑use image.

Solving the Visual Diagram Problem

Mermaid is a popular tool for authoring flowcharts, sequence diagrams, and more using plain text. However, many AI assistants return only the textual description of a diagram, leaving users to render it manually. The MCP server automates this step: an assistant can simply call the tool, pass the Mermaid code it produced, and receive a PNG that can be embedded in a chat, documentation, or UI. This eliminates the friction of manual rendering and ensures consistent styling across different platforms.

Core Functionality & Value

• Headless Rendering: Uses Puppeteer to launch a minimal Chromium instance, render the diagram as SVG, and capture it as PNG. This guarantees that the output matches what a user would see in a browser, with full support for CSS and theme overrides.
• Theme & Styling Flexibility: Supports built‑in themes (, , , ) and allows custom background colors, giving developers control over the visual tone without editing Mermaid code.
• MCP‑Ready Interface: Exposes a single tool that accepts parameters for code, theme, background color, and optional file naming. The tool adapts to the flag, either returning the image inline or saving it to disk—making it compatible with both desktop assistants that can handle binary blobs and server‑side workflows that prefer file storage.
• Robust Error Reporting: Provides detailed error messages if rendering fails, which helps developers diagnose issues with malformed Mermaid syntax or missing dependencies.

Use Cases & Real‑World Scenarios

• Interactive Documentation: AI assistants can answer “show me a flowchart of the deployment pipeline” by generating an up‑to‑date diagram directly in the conversation.
• Live Code Review: Developers can request visualizations of architecture diagrams from a codebase, and the assistant returns PNGs that can be embedded in pull requests or chat threads.
• Educational Tools: Tutors using AI to explain algorithms can have the assistant produce step‑by‑step flowcharts that students can view instantly.
• CI/CD Pipelines: Automated build scripts can invoke the MCP server to generate status diagrams (e.g., pipeline stages) and attach them to build reports.

Integration into AI Workflows

The server fits seamlessly into existing MCP‑based toolchains. A Claude or Cursor agent can declare the server in its configuration, and any subsequent prompt that generates Mermaid code can be passed to the tool. The returned PNG can then be streamed back to the user or written to a shared folder for further processing. Because the server runs on stdio, it can be launched locally or deployed in Docker containers, with optional Chrome dependency handling for CI environments.

Unique Advantages

• Zero Client‑Side Rendering: Clients do not need to bundle Puppeteer or a headless browser; the heavy lifting is offloaded to the server.
• Portable & Docker‑Friendly: Built with Puppeteer’s bundled Chromium by default, the server works out of the box in most containerized setups, and it provides clear guidance for handling Chrome dependencies when needed.
• Customizable Output: The ability to specify background colors and themes directly via parameters allows developers to match branding or accessibility requirements without post‑processing.

In summary, the Mermaid MCP Server empowers AI assistants to deliver instant, high‑quality diagram visuals, enhancing user experience and streamlining workflows that require dynamic visual content.