MCP server
by rtuin
Validate and render Mermaid diagrams as SVG images using Mermaid JS. Get clear error messages to improve your JavaScript
Validates Mermaid diagram syntax and renders them as SVG images, providing detailed error messages when diagrams are invalid.
Mermaid Validator is a community-built MCP server published by rtuin that provides AI assistants with tools and capabilities via the Model Context Protocol. Validate and render Mermaid diagrams as SVG images using Mermaid JS. Get clear error messages to improve your JavaScript It is categorized under developer tools.
You can install Mermaid Validator in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Mermaid Validator is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Mermaid Validator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Mermaid Validator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Mermaid Validator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired Mermaid Validator into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Mermaid Validator benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Mermaid Validator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: Mermaid Validator surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Mermaid Validator has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Mermaid Validator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Mermaid Validator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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A Model Context Protocol server that validates and renders Mermaid diagrams. This server enables LLMs to validate and render Mermaid diagrams.
You can configure your MCP client to use the Mermaid Validator by adding it to your mcp servers file:
{
"mcpServers": {
"mermaid-validator": {
"command": "npx",
"args": [
"-y",
"@rtuin/mcp-mermaid-validator@latest"
]
}
}
}
This project is structured as a simple TypeScript Node.js application that:
mcp-mermaid-validator/
├── dist/ # Compiled JavaScript output
│ └── main.js # Compiled main application
├── src/ # TypeScript source code
│ └── main.ts # Main application entry point
├── node_modules/ # Dependencies
├── package.json # Project dependencies and scripts
├── package-lock.json # Dependency lock file
├── tsconfig.json # TypeScript configuration
├── eslint.config.js # ESLint configuration
├── .prettierrc # Prettier configuration
└── README.md # Project documentation
The core functionality is implemented in src/main.ts. This component:
validateMermaid tool that accepts Mermaid diagram syntaxPurpose: Validates a Mermaid diagram and returns the rendered PNG if valid
Parameters:
diagram (string): The Mermaid diagram syntax to validateReturn Value:
{
content: [
{
type: "text",
text: "Mermaid diagram is valid"
},
{
type: "image",
data: string, // Base64-encoded PNG
mimeType: "image/png"
}
]
}
{
content: [
{
type: "text",
text: "Mermaid diagram is invalid"
},
{
type: "text",
text: string // Error message
},
{
type: "text",
text: string // Detailed error output (if available)
}
]
}
MCP Integration: The project uses the Model Context Protocol to standardize the interface for AI tools, allowing seamless integration with compatible clients.
PNG Output Format: The implementation uses PNG as the default output format to ensure better compatibility with most MCP clients, particularly Cursor, which doesn't support SVG.
Child Process Approach: The implementation uses Node.js child processes to interact with the Mermaid CLI, which provides:
Error Handling Strategy: The implementation uses a nested try-catch structure to:
Simple Project Structure: The project uses a straightforward TypeScript project structure for:
The application can be built and run using npm scripts:
# Install dependencies
npm install
# Build the application
npm run build
# Run locally (for development)
npx @modelcontextprotocol/inspector node dist/main.js
# Format code
npm run format
# Lint code
npm run lint
# Watch for changes (development)
npm run watch
The application runs as an MCP server that communicates via standard input/output, making it suitable for integration with MCP-compatible clients.
To release a new version, the following steps in order:
npm run buildnpm run bumpnpm run changelognpm publish --access public/dev/stdin, which can fail on WSL with ENXIO. This server now uses - for stdin/stdout (-i - / -o -) to be portable across Linux/macOS/WSL/Windows.npx @modelcontextprotocol/inspector npx -y @rtuin/mcp-mermaid-validator@latest or use an absolute path to dist/main.js).Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.