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hustcc/mcp-mermaid

by Various

❤️ Generate mermaid diagram and chart with AI MCP dynamically.

H

MCP

hustcc/mcp-mermaid

Added 1 June 2026

#mcp #mcp-server #mermaid #mermaidjs

Overview

An MCP (Model Context Protocol) server that generates Mermaid diagrams and charts dynamically. It accepts natural language descriptions from AI assistants and returns Mermaid code, enabling automatic diagram creation within chat or development workflows.

Best for

Best for
Developers using AI assistants who need on-demand diagrams for documentation, design, or debugging.

Use cases

  • Generate flowcharts or sequence diagrams from natural language prompts
  • Create architecture diagrams on demand during AI-assisted documentation
  • Produce Mermaid charts for inclusion in markdown or code comments

How to use

Install

npm install -g mcp-mermaid

Tested with

Cline, VS Code

Example client config

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

Notes

An MCP (Model Context Protocol) server that generates Mermaid diagrams and charts dynamically. It accepts natural language descriptions from AI assistants and returns Mermaid code, enabling automatic diagram creation within chat or development workflows.

572 stars on GitHub. Last updated 2026-05-15. Licensed MIT.

Use cases

  • Generate flowcharts or sequence diagrams from natural language prompts
  • Create architecture diagrams on demand during AI-assisted documentation
  • Produce Mermaid charts for inclusion in markdown or code comments

Pros

  • Enables dynamic diagram generation without manual drawing
  • Integrates with MCP-compatible AI assistants for seamless workflow
  • Written in TypeScript, making it easy to audit and extend

Cons

  • Output is limited to Mermaid syntax, not generic graphics
  • Requires an MCP-capable AI environment to function
  • Dependent on the underlying AI model’s interpretation accuracy

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Enables dynamic diagram generation without manual drawing
  • Integrates with MCP-compatible AI assistants for seamless workflow
  • Written in TypeScript, making it easy to audit and extend

Cons

  • Output is limited to Mermaid syntax, not generic graphics
  • Requires an MCP-capable AI environment to function
  • Dependent on the underlying AI model's interpretation accuracy
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