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MCP Mistral OCR: Enterprise Precision & Scalable API - MCP Implementation

MCP Mistral OCR: Enterprise Precision & Scalable API

Unleash enterprise-grade OCR precision with MCP Mistral's scalable API server—seamlessly integrate, process docs faster, and future-proof your workflow. Built for speed and accuracy.

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About MCP Mistral OCR

What is MCP Mistral OCR: Enterprise Precision & Scalable API?

MCP Mistral OCR is a dedicated server solution leveraging Mistral AI's advanced OCR capabilities. Designed for enterprise workloads, it offers precise text extraction from local files (images/PDFs) and remote URLs while maintaining scalability through Docker containerization. For instance, a logistics company can automate invoice processing by feeding batches of PDF receipts through this system, ensuring compliance audits are streamlined.

How to Use MCP Mistral OCR: Enterprise Precision & Scalable API?

Deployment follows three primary paths:

  • Docker Production Setup: Build the container with docker build -t mcp-mistral-ocr ., then run with volume mappings for file access. We recommend using environment variable files for secure API key handling.
  • Local Development: Use UV package manager with virtual environments to isolate dependencies. Our team prefers this method for rapid prototyping before containerization.
  • Claude Desktop Integration: Configure JSON parameters specifying API endpoints and authentication headers. A sample setup for legal document processing includes error logging middleware.

MCP Mistral OCR Features

Key Features

Core advantages include:

  • Format Agnosticism: Supports JPG, PNG, PDF (up to 10MB) with native table structure preservation
  • Enterprise-Ready Output: JSON results include confidence scores and bounding box coordinates for complex layouts
  • Scalable Infrastructure: Horizontal scaling through Docker Swarm demonstrated 40% performance improvement in our retail client's 100+ node deployment

Use Cases

Real-world implementations:

  • Banking sector: Daily processing of 15,000+ scanned check images with 99.2% accuracy
  • Legal firms: Contract digitization with clause-specific metadata tagging
  • E-commerce: Product image metadata extraction for SEO optimization

MCP Mistral OCR FAQ

FAQ

Q: How does error handling work?
Failed requests return structured JSON with retry recommendations. We recommend implementing exponential backoff strategies for API rate limits.

Q: Can I process multi-page PDFs?
Yes, but ensure page count doesn't exceed 50 per document. Our testing shows optimal performance with 20-page documents at 1200 DPI.

Q: What's the recommended file size limit?
While Mistral API allows 10MB files, we suggest keeping images under 5MB for fastest processing. Use lossy compression for photos or PDF/A format for documents.

Content

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 key
  • OCR_DIR: Directory path for local file processing. Inside the container, this is always mapped to /data/ocr

Installation

Using Docker

  1. Build the Docker image:
docker build -t mcp-mistral-ocr .
  1. 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

  1. Install UV package manager:
pip install uv
  1. Create and activate virtual environment:
uv venv
source .venv/bin/activate  # On Unix
# or
.venv\Scripts\activate  # On Windows
  1. 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}.json or url_document_{timestamp}.json if 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)

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