Fast PaddleOCR MCP server - Extract text from images using PaddleOCR with optimized performance
Project description
PaddleOCR-MCP
PaddleOCR MCP (Model Context Protocol) server that extracts text from images and outputs results in markdown format. Optimized for fast inference with GPU auto-detection.
Installation
Using uvx (Recommended - No Installation Needed)
# Run MCP server directly
uvx fast-paddleocr-mcp
Or Install from PyPI
pip install fast-paddleocr-mcp
fast-paddleocr-mcp
MCP Server Configuration
MCP Tool: ocr_image
The server provides a single tool called ocr_image that:
- Input:
image_path(string) - Path to the input image file - Output: Returns the path to the generated markdown file containing OCR results
Integration with MCP Clients
To use this server with an MCP client (like Cursor, Claude Desktop, etc.), configure it in your MCP settings:
{
"mcpServers": {
"paddleocr": {
"command": "uvx",
"args": ["fast-paddleocr-mcp"]
}
}
}
MCP Request/Response Example
Request:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "ocr_image",
"arguments": {
"image_path": "test_image.png"
}
}
}
Response:
{
"jsonrpc": "2.0",
"id": 1,
"result": {
"content": [
{
"type": "text",
"text": "test_image.png.md"
}
]
}
}
Default Optimization Settings
The MCP server uses optimized default settings for fast inference:
- ✅ Fast mode enabled: Disables textline orientation classification (skips one model)
- ✅ PP-OCRv4: Uses faster mobile models (PP-OCRv4_mobile_det, PP-OCRv4_mobile_rec)
- ✅ 640px image size limit: Faster processing (vs default 960px)
- ✅ Auto GPU detection: Automatically uses GPU if available, falls back to CPU
- ✅ Document preprocessing disabled: Skips unnecessary preprocessing steps
Output Format
The generated markdown file contains:
- Source image path
- List of detected text (one per line)
Example output (test_image.png.md):
# OCR Result
**Source Image:** `test_image.png`
---
- HelloPaddleOcR
- 10000C
Requirements
- Python >= 3.8
- PaddleOCR
- PaddlePaddle
- Pillow
License
MIT
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