mcp-pandoc: A Document Conversion MCP Server

Overview: What is mcp-pandoc MCP Server?

mcp-pandoc is an MCP (Model Context Protocol) server designed to facilitate document format conversion between various formats, such as Markdown, HTML, PDF, DOCX, RST, LaTeX, and EPUB. It leverages Pandoc, a powerful document transformation tool known for its versatility in handling different document types. This server integrates seamlessly into the broader MCP ecosystem, allowing AI applications like Claude Desktop to connect with it through standardized protocols.

🔧 Core Features & MCP Capabilities

mcp-pandoc offers robust features that cater to diverse conversion needs. Users can easily transform content between different formats by providing input and output paths or contents directly. The server supports both basic and advanced document types, enabling the handling of complex documents with intricate formatting requirements. As part of the Model Context Protocol, mcp-pandoc ensures compatibility across various AI applications, making it a valuable tool for developers looking to enhance their AI workflows.

Supported Document Formats

• Basic formats: plain text (.txt), Markdown (.md), HTML (.html)
• Advanced formats:
  • PDF (.pdf) - requires TeX Live installation
  • DOCX (.docx)
  • RST (.rst)
  • LaTeX (.tex)
  • EPUB (.epub)

Key Capabilities of mcp-pandoc

1. Versatile Document Transformation: Supports a wide range of document types, ensuring that users can convert content from one format to another efficiently.
2. Enhanced Functionality with Pandoc: Built on top of the robust Pandoc library, providing advanced features for handling complex formatting and structure preservation.
3. Integrated with MCP Protocol: Allows seamless interaction between mcp-pandoc and other AI applications via the Model Context Protocol.

⚙️ MCP Architecture & Protocol Implementation

mcp-pandoc is designed following the principles of the Model Context Protocol (MCP), which ensures interoperability among various tools and applications. The server operates by accepting commands through standard input/output streams, allowing it to be easily integrated into AI application environments. The key architectural components include:

1. Command Interface: Accepts commands for document conversion in a standardized format.
2. Pandoc Integration: Utilizes Pandoc's powerful capabilities via the Pandoc Python package for seamless document transformations.
3. MCP Compliance: Ensures compatibility and interoperability with other MCP servers and clients, enhancing the overall ecosystem.

Mermaid Diagram: MCP Protocol Flow

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[mcp-pandoc]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Mermaid Diagram: Data Architecture

graph TD
    Database(Storage) -->|Data Flow|mcp-pandoc(Server)
    mcp-pandoc(Server) -->|Processed Data|AI Application(AI Workload)
    style Database fill:#f7dce5
    style mcp-pandoc fill:#e8f3f1
    style AI Application fill:#fcddbf

🚀 Getting Started with Installation

To get started, users can either install the latest published version of mcp-pandoc via Smithery or configure it manually in their MCP client. Here are detailed steps for both methods:

Option 1: Installing manaully using claude_desktop_config.json

On MacOS:

open ~/Library/Application\ Support/Claude/claude_desktop_config.json

On Windows:

%APPDATA%/Claude/claude_desktop_config.json

1. Local Configuration: Modify the configuration to include mcp-pandoc as follows:

   "mcpServers": {
     "mcp-pandoc": {
       "command": "uv",
       "args": [
         "--directory",
         "<DIRECTORY>/mcp-pandoc",
         "run",
         "mcp-pandoc"
       ]
     }
   }
   

2. Published Configuration: Replace with the public configuration as follows:

   "mcpServers": {
     "mcp-pandoc": {
       "command": "uvx",
       "args": [
         "mcp-pandoc"
       ]
     }
   }
   

Option 2: Using Smithery for Installation

To install mcp-pandoc via Smithery, run the following command:

npx @modelcontextprotocol/inspector uv --directory /Users/vivekvells/Desktop/code/ai/mcp-pandoc run mcp-pandoc

Upon launching, you can access the MCP Inspector through a browser to debug and manage your server.

💡 Key Use Cases in AI Workflows

mcp-pandoc is particularly useful in various AI workflow scenarios where document conversions are required. Here’s how it can be leveraged:

1. Collaborative Writing: Authors working on multiple documents in different formats can use mcp-pandoc to reconcile their work across Markdown and HTML files.
2. Report Generation: Businesses creating detailed reports may benefit from converting raw data into structured PDFs for easier distribution.

🔌 Integration with MCP Clients

mcp-pandoc is compatible with several MCP clients, including Claude Desktop, Continue, and Cursor, as shown in the compatibility matrix below:

MCP Client Compatibility Matrix

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

📊 Performance & Compatibility Matrix

mcp-pandoc is designed to handle a variety of document types efficiently, ensuring seamless compatibility with different tools and APIs. The performance matrix indicates how well it integrates with various external systems.

Example Configuration Code

{
  "mcpServers": {
    "pandoc-conversion-server": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-pandoc"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

🛠️ Advanced Configuration & Security

For advanced users, mcp-pandoc provides extensive configuration options and enhanced security measures. Ensuring that sensitive data remains secure is a priority, especially when handling complex documents.

Configuration Sample

{
  "mcpServers": {
    "pandoc-conversion-server": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-pandoc"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

1. Q: What is the difference between basic and advanced document types?

   • A: Basic document types such as plain text, Markdown, and HTML are simpler structures with limited formatting options. Advanced types like PDF, DOCX, RST, LaTeX, and EPUB support more complex layouts and features.

2. Q: How do I securely configure mcp-pandoc?

   • A: Secure configuration involves setting up environment variables such as API_KEY to restrict access to sensitive operations. Ensure that all secrets are stored securely and used only in appropriate contexts.

3. Q: Can mcop-pandoc handle real-world document types?

   • A: Yes, mcp-pandoc is designed to handle a wide range of document formats commonly found in real-world applications, ensuring compatibility with diverse input sources.

4. Q: What are the main constraints when integrating MCP servers like mcp-pandoc?

   • A: Main constraints include ensuring proper configuration and robust error handling. Compatibility issues might arise if the clients or tools do not support certain document formats.

5. Q: How can developers contribute to improving mcp-pandoc?

   • A: Developers can report bugs, suggest features, and submit pull requests through our GitHub repository. Regular contributions help evolve the software and meet user needs better.

👨‍💻 Development & Contribution Guidelines

We encourage contributions from the community to enhance the capabilities of mcp-pandoc. Here’s how you can contribute:

1. Report Issues: Open issues on our GitHub Issues page.
2. Submit Pull Requests: Create pull requests to add features or fix bugs.

🌐 MCP Ecosystem & Resources

For more information about the Model Context Protocol and its ecosystem, visit our official documentation:

• Model Context Protocol (MCP)

This comprehensive guide positions mcp-pandoc as a versatile and essential tool for developers working with AI applications and MCP integrations.