universal-document-mcp/scripts/mcp_server_config.json

Universal Document Converter MCP Server - AI-powered markdown to PDF conversion with Mermaid diagram support for Claude Desktop, Cline, and other MCP clients

{
  "name": "universal-document-converter",
  "version": "1.0.0",
  "description": "Universal MCP Server for MD -> HTML -> PDF conversion with Mermaid optimization",
  "author": "AUGMENT AI Assistant",
  "license": "MIT",
  
  "server": {
    "command": "python",
    "args": ["mcp_universal_document_converter.py"],
    "env": {
      "PYTHONPATH": ".",
      "LOG_LEVEL": "INFO"
    }
  },
  
  "tools": [
    {
      "name": "convert_document_md_to_pdf",
      "description": "Universal document converter: MD -> HTML -> PDF with Mermaid optimization",
      "triggers": [
        "convert: md -> html -> pdf",
        "markdown to pdf",
        "document conversion", 
        "md to pdf",
        "convert markdown",
        "generate pdf",
        "mermaid pdf",
        "export pdf",
        "create pdf from markdown",
        "markdown document conversion"
      ],
      "inputSchema": {
        "type": "object",
        "properties": {
          "markdown_file": {
            "type": "string",
            "description": "Path to the markdown file to convert (relative to workspace)"
          },
          "optimize_diagrams": {
            "type": "boolean",
            "description": "Whether to optimize Mermaid diagrams for better PDF rendering",
            "default": true
          },
          "user_input": {
            "type": "string", 
            "description": "Original user input to check for trigger keywords"
          }
        },
        "required": ["markdown_file"]
      },
      "outputSchema": {
        "type": "object",
        "properties": {
          "success": {
            "type": "boolean",
            "description": "Whether the conversion was successful"
          },
          "input_file": {
            "type": "string",
            "description": "Path to the input markdown file"
          },
          "output_file": {
            "type": "string", 
            "description": "Path to the generated PDF file"
          },
          "backup_file": {
            "type": "string",
            "description": "Path to the backup of the original file"
          },
          "script_file": {
            "type": "string",
            "description": "Path to the generated conversion script"
          },
          "file_size_kb": {
            "type": "number",
            "description": "Size of the generated PDF in KB"
          },
          "analysis": {
            "type": "object",
            "description": "Document analysis results"
          },
          "optimized": {
            "type": "boolean",
            "description": "Whether diagrams were optimized"
          },
          "message": {
            "type": "string",
            "description": "Detailed success message with file information"
          },
          "error": {
            "type": "string",
            "description": "Error message if conversion failed"
          }
        }
      }
    }
  ],
  
  "capabilities": {
    "document_conversion": {
      "formats": ["markdown", "html", "pdf"],
      "diagram_support": ["mermaid"],
      "optimization": true,
      "backup_creation": true,
      "professional_formatting": true
    },
    "intelligent_features": {
      "automatic_diagram_optimization": true,
      "keyword_trigger_detection": true,
      "document_type_analysis": true,
      "smart_label_shortening": true,
      "responsive_diagram_sizing": true
    },
    "output_features": {
      "a4_format": true,
      "custom_margins": "0.75 inches",
      "print_optimization": true,
      "page_break_handling": true,
      "svg_diagram_rendering": true
    }
  },
  
  "dependencies": {
    "python_packages": ["playwright", "markdown"],
    "system_requirements": ["chromium"],
    "auto_install": true
  },
  
  "usage_examples": [
    {
      "trigger": "convert: md -> html -> pdf",
      "description": "Basic conversion trigger",
      "example": "I need to convert: md -> html -> pdf for my document.md file"
    },
    {
      "trigger": "markdown to pdf", 
      "description": "Simple conversion request",
      "example": "Can you convert this markdown to pdf?"
    },
    {
      "trigger": "document conversion",
      "description": "General conversion request", 
      "example": "I need document conversion for my technical paper"
    },
    {
      "trigger": "mermaid pdf",
      "description": "Mermaid-specific conversion",
      "example": "Generate a mermaid pdf from my architecture document"
    }
  ],
  
  "integration": {
    "vscode_extension": "AUGMENT",
    "activation_method": "keyword_detection",
    "workspace_relative_paths": true,
    "automatic_backup": true,
    "progress_reporting": true
  }
}