📄 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

Tool	Description	Input Parameters	Returns
`read_pdf_text`	Extracts normal text from PDF pages	`file_path`, `start_page`, `end_page`	List of page texts
`read_by_ocr`	Recognizes text via OCR	`file_path`, `start_page`, `end_page`, `language`, `dpi`	OCR extracted text
`read_pdf_images`	Extracts images from a PDF page	`file_path`, `page_number`	List 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.