ComPDF AI (Formerly ComIDP) for MCP Server

As part of the KDAN ecosystem, ComPDF AI for MCP Server delivers Intelligent Document Extraction—automatically extracting key information from unstructured documents (such as PDFs or images), converting it into structured data, and supporting batch processing to significantly boost document handling efficiency.

If you find this library helpful, please consider giving us a ⭐ Star on GitHub! Have feedback or questions? Join the conversation in our Discussions.

Why ComPDF AI for MCP Server?

• Batch Processing for Real Efficiency: Handle large volumes of documents at once. Batch processing significantly speeds up your workflow and reduces operational overhead.

• From Unstructured to Actionable: Transform messy PDFs and scanned images into structured, machine-readable data that can be easily used in databases, analytics, or downstream applications.

• Boost Document Handling Productivity: Eliminate bottlenecks in document processing. Focus on insights and decisions, while ComPDF AI handles the extraction automatically and accurately.

• Native MCP Server Architecture: Designed as an MCP server, it seamlessly integrates with any MCP‑compatible client, enabling standardized, context‑aware document intelligence workflows and effortless scalability.

Table of Contents

• Free Trial and License
• What is ComPDF AI for MCP Server
• ComPDF AI MCP Server for Claude Desktop
• • Setup
  • API Reference
• Support
• Changelog

Free Trial and License

This project is licensed under the Apache License 2.0. Please contact us for a trial license key.

What is ComPDF AI for MCP Server

ComPDF AI for MCP Server is a lightweight Model Context Protocol (MCP) server designed for seamless integrating ComPDF AI with AI chatbots, providing unstructured document processing functionalities, such as extracting data from PDF files. The service returns results in structured plain-text format, enabling downstream processing or archival.

ComPDF AI MCP Server for Claude Desktop

Setup

1. Dependencies:

• Ensure you have the following dependencies installed:

  • Python 3.10 or higher

  • pip (Python package installer)

  • uv

    pip install uv 

• Create a virtual environment and install the required packages:

  • Windows:

  cd comidp-mcp\\src
  python -m venv .venv
  .venv\\Scripts\\activate
  pip install -r requirements.txt

  • Linux / MacOS:

  cd comidp-mcp/src
  python -m venv .venv
  source .venv/bin/activate
  pip install -r requirements.txt

2. Configure Claude Desktop

   To configure the integration with Claude Desktop, you need to edit the claude_desktop_config.json file.

   If the file does not already exist, you can create and open it directly from Claude Desktop by following these steps:

   1. Open Claude Desktop.

   2. Click the Claude icon in the top-left corner of the window.

   3. Navigate to File → Settings → Developer → Edit Config.

   This will automatically open (or create) the claude_desktop_config.json file in your system's default editor.

   Once the file is open, you can add your configuration for the comidp-mcp tool as needed. Then you can add a comidp-mcp server configuration in mcpServers section of the file. Here is an example configuration:

   {
       "mcpServers": { 
           "comidp-mcp": {     
               "command": "uv", 
               "args": [
                       "run", 
                       "PATH/TO/comidp-mcp/src/virtual environment python",
                       "PATH/TO/comidp-mcp/src/comidp_tools.py"
               ],
               "env": {
                   "IDPKEY": "your_idp_key_here"
               }
           }
       }
   }

   • Note:
     1. The virtual environment python path should point to the Python executable in your virtual environment. It should look like
        • For Windows C:\\path\\to\\comidp-mcp\\.venv\\Scripts\\python.exe.
        • For Linux/MacOS /path/to/comidp-mcp/.venv/bin/python.
     2. All paths should be absolute paths.
     3. Replace your_idp_key_here with your actual IDPKEY API key.

3. Restart Claude Desktop.

API Reference

Data extraction

def data_extraction(filenames: list, save_dir_path: str = "output", key: str = "", err_msg_lang: str = "en") -> Dict[str, str]:
    """
    Extract data from PDF files and save to TXT files in the specified folder.

    Params:
        filenames: A list of PDF file paths.
        save_dir_path: Folder where the result TXT files will be saved.
        key: The API key for IDPKEY. Required on the first call.
        err_msg_lang: Optional language code for error messages (e.g., 'zh' or 'en'). Defaults to 'en'.

    Returns:
        A dictionary mapping each input file path to its corresponding output TXT file path.
        If an error occurs, the value will be an error message.
    """

def data_extraction_from_folder(folder: str, save_dir_path: str, recursive: bool = False, key: str = "", err_msg_lang: str = "en") -> Dict[str, str]:
    """
    Extract data from PDF files in a folder and save to TXT files in the specified folder.

    Params:
        folder: Path to the folder containing PDF files.
        save_dir_path: Path to the folder where the result files will be saved.
        key: The API key for IDPKEY. Required on the first call.
        recursive: If true, recursively search subdirectories for PDF files.
        err_msg_lang: Optional language code for error messages (e.g., 'zh' or 'en'). Defaults to 'en'.

    Returns:
        A dictionary mapping each input file path to its corresponding output TXT file path.
        If an error occurs, the value will be an error message.
    """

Support

If you encounter any issues or need support, please open an issue or contact our team.

Changelog

You can click to see the version changes of ComPDF AI.