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MCP PDF Server

by DeepSeekMine
GitHub
Python
6
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Integrations

  • Enables reading and processing PDF files with tools for text extraction, OCR recognition, and image extraction from PDF documents.

  • Based on FastMCP framework which is hosted on GitHub, allowing users to leverage the MCP protocol implementation for PDF processing.

  • Requires Python 3.9+ environment to run the server, utilizing Python libraries like PyMuPDF for PDF processing functionality.

📄 MCP PDF Server

A PDF file reading server based on FastMCP.

Supports PDF text extraction, OCR recognition, and image extraction via the MCP protocol, with a built-in web debugger for easy testing.

🚀 Features

  • read_pdf_text
    Extracts normal text from a PDF (page by page).
  • read_by_ocr
    Uses OCR to recognize text from scanned or image-based PDFs.
  • read_pdf_images
    Extracts all images from a specified PDF page (Base64 encoded output).

📂 Project Structure

mcp-pdf-server/ ├── pdf_resources/ # Directory for uploaded and processed PDF files ├── txt_server.py # Main server entry point └── README.md # Project documentation

⚙️ Installation

Recommended Python version: 3.9+

pip install pymupdf mcp

Note: To use OCR features, you may need a MuPDF build with OCR support or external OCR libraries.

🔦 Start the Server

Run the following command:

python txt_server.py

You should see logs like:

Serving on http://127.0.0.1:6231

🌐 Web Debugging Interface

Open your browser and visit:

http://127.0.0.1:6231
  • Select a tool from the left panel
  • Fill in parameters on the right panel
  • Click "Run" to test the tool

No coding required — easily debug and test via the web UI.

🛠️ API Tool List

ToolDescriptionInput ParametersReturns
read_pdf_textExtracts normal text from PDF pagesfile_path, start_page, end_pageList of page texts
read_by_ocrRecognizes text via OCRfile_path, start_page, end_page, language, dpiOCR extracted text
read_pdf_imagesExtracts images from a PDF pagefile_path, page_numberList of images (Base64 encoded)

📝 Example Usage

Extract text from pages 1 to 5:

mcp run read_pdf_text --args '{"file_path": "pdf_resources/example.pdf", "start_page": 1, "end_page": 5}'

Perform OCR recognition on page 1:

mcp run read_by_ocr --args '{"file_path": "pdf_resources/example.pdf", "start_page": 1, "end_page": 1, "language": "eng"}'

Extract all images from page 3:

mcp run read_pdf_images --args '{"file_path": "pdf_resources/example.pdf", "page_number": 3}'

📢 Notes

  • Files must be placed inside the pdf_resources/ directory, or an absolute path must be provided.
  • OCR functionality requires appropriate OCR support in the environment.
  • When processing large files, adjust memory and timeout settings as needed.

📜 License

This project is licensed under the MIT License.
For commercial use, please credit the original source.

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A PDF processing server that extracts text via normal parsing or OCR, and retrieves images from PDF files through the MCP protocol with a built-in web debugger.

  1. 🚀 Features
    1. 📂 Project Structure
      1. ⚙️ Installation
        1. 🔦 Start the Server
          1. 🌐 Web Debugging Interface
            1. 🛠️ API Tool List
              1. 📝 Example Usage
                1. 📢 Notes
                  1. 📜 License

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