# 🧠 Contributing to `mcp-ocr`
Thanks for your interest in contributing to **mcp-ocr**! 🎉
We welcome all kinds of contributions—bug reports, feature suggestions, code improvements, documentation updates, or just fixing typos.
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## 📌 Project Overview
**`mcp-ocr`** is an advanced OCR server built on the **Model Context Protocol (MCP)**. It allows model-to-model and agent-to-agent communication via OCR inference endpoints, supporting real-time text extraction workflows in distributed AI systems.
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## 🧑💻 How to Contribute
### 1. 🔍 Reporting Issues
If you encounter a bug or unexpected behavior, open an issue with:
* Clear title
* Reproduction steps
* Expected vs actual behavior
* Screenshots (if applicable)
* Your environment (OS, Python version, etc.)
### 2. 🌱 Suggesting Enhancements
Have a feature idea? Submit an issue and prefix the title with `[Feature]`. Explain the problem it solves and your proposed solution.
### 3. 🛠️ Code Contributions
We follow the [GitHub Flow](https://guides.github.com/introduction/flow/). Here’s how to contribute code:
#### Step-by-Step:
1. **Fork** the repo and clone it.
2. Set up your dev environment:
```bash
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
3. Create a new branch:
```bash
git checkout -b feature/your-feature-name
```
4. Make your changes and commit:
```bash
git commit -m "feat: brief message about your change"
```
5. Push to your fork and open a **Pull Request**.
#### Code Standards:
* Use `black` and `ruff` for formatting/linting.
* Write meaningful commit messages.
* Document your changes (code + markdown if needed).
* Include tests if adding new functionality.
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## 🙏 Code of Conduct
We follow the [Contributor Covenant](https://www.contributor-covenant.org/).
Please be respectful in all communications and reviews.
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## 📬 Questions?
For discussions, use:
* GitHub Discussions (if enabled)
* Or open an issue with `[Question]` in the title
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## 🚀 Contributors
Every contributor is **valued and credited**.
Let’s build something amazing together!
