A Model Context Protocol server that validates and renders Mermaid diagrams.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"mermaid-validator": {
"args": [
"-y",
"@rtuin/mcp-mermaid-validator@latest"
],
"command": "npx"
}
}
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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.
No automated test available for this server. Check the GitHub README for setup instructions.
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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