
mcp mistral ocr
Model Context Protocol (MCP) Server for Mistral OCR API
Repository Info
About This Server
Model Context Protocol (MCP) Server for Mistral OCR API
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
Documentation
MCP Mistral OCR
An MCP server that provides OCR capabilities using Mistral AI's OCR API. This server can process both local files and URLs, supporting images and PDFs.
Features
- Process local files (images and PDFs) using Mistral's OCR
- Process files from URLs with explicit file type specification
- Support for multiple file formats (JPG, PNG, PDF, etc.)
- Results saved as JSON files with timestamps
- Docker containerization
- UV package management
Environment Variables
MISTRAL_API_KEY: Your Mistral AI API keyOCR_DIR: Directory path for local file processing. Inside the container, this is always mapped to/data/ocr
Installation
Installing via Smithery
To install Mistral OCR for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @everaldo/mcp/mistral-crosswalk --client claude
Using Docker
- Build the Docker image:
docker build -t mcp-mistral-ocr .
- Run the container:
docker run -e MISTRAL_API_KEY=your_api_key -e OCR_DIR=/data/ocr -v /path/to/local/files:/data/ocr mcp-mistral-ocr
Local Development
- Install UV package manager:
pip install uv
- Create and activate virtual environment:
uv venv
source .venv/bin/activate # On Unix
# or
.venv\Scripts\activate # On Windows
- Install dependencies:
uv pip install .
Claude Desktop Configuration
Add this configuration to your claude_desktop_config.json:
{
"mcpServers": {
"mistral-ocr": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MISTRAL_API_KEY",
"-e",
"OCR_DIR",
"-v",
"C:/path/to/your/files:/data/ocr",
"mcp-mistral-ocr:latest"
],
"env": {
"MISTRAL_API_KEY": "<YOUR_MISTRAL_API_KEY>",
"OCR_DIR": "C:/path/to/your/files"
}
}
}
}
Available Tools
1. process_local_file
Process a file from the configured OCR_DIR directory.
{
"name": "process_local_file",
"arguments": {
"filename": "document.pdf"
}
}
2. process_url_file
Process a file from a URL. Requires explicit file type specification.
{
"name": "process_url_file",
"arguments": {
"url": "https://example.com/document",
"file_type": "image" // or "pdf"
}
}
Output
OCR results are saved in JSON format in the output directory inside OCR_DIR. Each result file is named using the following format:
- For local files:
{original_filename}_{timestamp}.json - For URLs:
{url_filename}_{timestamp}.jsonorurl_document_{timestamp}.jsonif no filename is found in the URL
The timestamp format is YYYYMMDD_HHMMSS.
Supported File Types
- Images: JPG, JPEG, PNG, GIF, WebP
- Documents: PDF and other document formats supported by Mistral OCR
Limitations
- Maximum file size: 50MB (enforced by Mistral API)
- Maximum document pages: 1000 (enforced by Mistral API)
Quick Start
Clone the repository
git clone https://github.com/everaldo/mcp-mistral-ocrInstall dependencies
cd mcp-mistral-ocr
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
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