A MCP server for OCR files using Mistral API
Project description
MCP OCR AI
Introduction
This repository contains an application that allows performing OCR (Optical Character Recognition) on various types of documents and images using the Mistral AI API. The application is designed to process files in formats such as PDF, Word, PowerPoint, images (JPEG, PNG, etc.), and other document formats.
Main Features:
- Support for multiple document and image formats.
- Use of the Mistral AI API for OCR processing.
- Caching of results to improve performance.
How to Set Up
- Add the key to the environment variable:
export MISTRAL_API_KEY="your_api_key_here"
- Configure the MCP server on ZED:
{
/// The name of your MCP server
"ocrai": {
/// The command which runs the MCP server
"command": "uvx",
/// The arguments to pass to the MCP server
"args": ["mcp_ocrai"],
/// The environment variables to set
"env": {}
}
}
2. Alternatively, you can pass the API key directly via the command line:
```sh
mcp-ocrai --api-key "your_api_key_here"
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file mcp_ocrai-0.3.0.tar.gz.
File metadata
- Download URL: mcp_ocrai-0.3.0.tar.gz
- Upload date:
- Size: 16.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ae3d802872f14f19065189bbb25f221950ecb97befe0a1eca7ff22f254204bb3
|
|
| MD5 |
ad26f08c29039e20db7d8a1ddf5704e0
|
|
| BLAKE2b-256 |
0831044ce8d507227bbe14d6766bc3e90aa46a19ded466cdd63f8d709c1896e2
|
File details
Details for the file mcp_ocrai-0.3.0-py3-none-any.whl.
File metadata
- Download URL: mcp_ocrai-0.3.0-py3-none-any.whl
- Upload date:
- Size: 17.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.9.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f1ae4c5e4646a5f49d249aa0edb6733afb228d4872720e37d12ad0177bd2b527
|
|
| MD5 |
eadd014f477d05712d9394e8d739c0a1
|
|
| BLAKE2b-256 |
f960e0ce68523240289da62cbc7e088340c71324a8d784e9dd96b3617972ab10
|