lemopian
MCP Serverlemopianpublic

mistral ocr mcp

MCP Server Showcasing How to Use mistral Document OCR functionality

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About This Server

MCP Server Showcasing How to Use mistral Document OCR functionality

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

Mistral OCR MCP Server

A Model Context Protocol (MCP) server that provides OCR (Optical Character Recognition) functionality using Mistral's OCR API. This server allows you to extract text content from PDF files and images through MCP-compatible clients like Cursor and Claude Desktop.

📖 For more context and practical usage examples, read the related article: How I Use Mistral Document AI to Consolidate My Notes

Usage example flowchart

!flow

Features

  • Extract text from PDF files and images (JPG, JPEG, PNG, TIFF, BMP)
  • Returns structured content with page-by-page breakdown
  • Integrates seamlessly with MCP clients
  • Built with FastMCP for optimal performance

Prerequisites

  • uv package manager
  • Python 3.10.1 or higher
  • Mistral API Key : https://console.mistral.ai/api-keys

Installation

  1. Clone the repository:

    git clone https://github.com/lemopian/mistral-ocr-mcp.git
    cd mistral-ocr-mcp
    
  2. Install dependencies using uv:

    uv sync
    
  3. Set up environment variables: Create a .env file in the project root:

    echo "MISTRAL_API_KEY=your_mistral_api_key_here" > .env
    

Configuration for MCP Clients

Add the following configuration to your MCP client config file:

{
  "mcpServers": {
    "mistral-ocr": {
      "command": "/Users/yourusername/.local/bin/uv",
      "args": [
        "--directory",
        "/path/to/mistral-ocr-mcp",
        "run",
        "main.py"
      ]
    }
  }
}

Important: Replace /path/to/mistral-ocr-mcp with the actual path to your cloned repository.

Usage

Once configured, the server provides the following tool:

extract_file_content

Extracts text content from PDF files and images.

Parameters:

  • file_path (string): Local path to the PDF or image file

Returns:

  • Extracted text content as a string

Supported formats:

  • PDF files (.pdf)
  • Image files (.jpg, .jpeg, .png, .tiff, .bmp)

Example usage :

Please extract the text from this document: /path/to/your/document.pdf

Development

Running the server directly

uv run main.py

Project structure

mistral-ocr-mcp/
├── mistral_ocr/          # Package directory
│   ├── __init__.py       # Package initialization
│   └── extractor.py      # Mistral OCR functionality
├── docs/                 # Documentation
│   └── flowchart.png     # Architecture flowchart
├── main.py               # MCP server implementation
├── pyproject.toml        # Project dependencies and configuration
├── uv.lock              # Dependency lock file
├── .env                 # Environment variables (create this)
├── .gitignore           # Git ignore rules
└── README.md            # This file

Environment Variables

  • MISTRAL_API_KEY: Your Mistral API key (required)

Troubleshooting

  1. "MISTRAL_API_KEY must be set" error:

    • Ensure you've created a .env file with your Mistral API key
    • Verify the API key is valid
  2. "File not found" error:

    • Check that the file path is correct and accessible
    • Ensure the file format is supported
  3. MCP connection issues:

    • Verify the path to uv is correct in your MCP configuration
    • Ensure the repository path is absolute and correct
    • Check that all dependencies are installed with uv sync

Quick Start

1

Clone the repository

git clone https://github.com/lemopian/mistral-ocr-mcp
2

Install dependencies

cd mistral-ocr-mcp
npm install
3

Follow the documentation

Check the repository's README.md file for specific installation and usage instructions.

Repository Details

Ownerlemopian
Repomistral-ocr-mcp
LanguagePython
License-
Last fetched8/10/2025

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