PDF Reader

Integrates with PyPDF2 to enable efficient text extraction and information retrieval from PDF documents for various applications.

Installation Instructions

README: https://github.com/trafflux/pdf-reader-mcp

PDF Reader MCP Server

A Model Context Protocol (MCP) server that provides tools for reading and extracting text from PDF files, supporting both local files and URLs.

Author

Philip Van de Walker
Email: philip.vandewalker@gmail.com
GitHub: https://github.com/trafflux

Features

• Read text content from local PDF files
• Read text content from PDF URLs
• Error handling for corrupt or invalid PDFs
• Volume mounting for accessing local PDFs
• Auto-detection of PDF encoding
• Standardized JSON output format

Installation

1. Clone the repository:

git clone https://github.com/trafflux/pdf-reader-mcp.git
cd pdf-reader-mcp

2. Build the Docker image:

docker build -t mcp/pdf-reader .

Usage

Running the Server

To run the server with access to local PDF files:

docker run -i --rm -v /path/to/pdfs:/pdfs mcp/pdf-reader

Replace /path/to/pdfs with the actual path to your PDF files directory.

If not using local PDF files:

docker run -i --rm mcp/pdf-reader

MCP Configuration

Add to your MCP settings configuration:

{
  "mcpServers": {
    "pdf-reader": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "/path/to/pdfs:/pdfs",
        "mcp/pdf-reader"
      ],
      "disabled": false,
      "autoApprove": []
    }
  }
}

Without local file PDF files:

{
  "mcpServers": {
    "pdf-reader": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "mcp/pdf-reader"],
      "disabled": false,
      "autoApprove": []
    }
  }
}

Available Tools

1. read_local_pdf

   • Purpose: Read text content from a local PDF file
   • Input:

     {
       "path": "/pdfs/document.pdf"
     }
     

   • Output:

     {
       "success": true,
       "data": {
         "text": "Extracted content..."
       }
     }
     

2. read_pdf_url

   • Purpose: Read text content from a PDF URL
   • Input:

     {
       "url": "https://example.com/document.pdf"
     }
     

   • Output:

     {
       "success": true,
       "data": {
         "text": "Extracted content..."
       }
     }
     

Error Handling

The server handles various error cases with clear error messages:

• Invalid or corrupt PDF files
• Missing files
• Failed URL requests
• Permission issues
• Network connectivity problems

Error responses follow the format:

{
  "success": false,
  "error": "Detailed error message"
}

Dependencies

• Python 3.11+
• PyPDF2: PDF parsing and text extraction
• requests: HTTP client for fetching PDFs from URLs
• MCP SDK: Model Context Protocol implementation

Project Structure

.
├── Dockerfile          # Container configuration
├── README.md          # This documentation
├── requirements.txt   # Python dependencies
└── src/
    ├── __init__.py    # Package initialization
    └── server.py      # Main server implementation

License

Copyright 2025 Philip Van de Walker

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Contact

For questions, issues, or contributions, please contact Philip Van de Walker:

• Email: philip.vandewalker@gmail.com
• GitHub: https://github.com/trafflux