What is the Atlan AI Agent Toolkit?

The Atlan AI Agent Toolkit is a collection of tools and protocols designed to enable AI agents to interact with Atlan services, providing them with the context needed to perform tasks effectively.

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is a standardized protocol that allows AI models to access and interact with external data sources and tools, facilitating function calling, asset search, and data retrieval.

How does the Atlan AI Agent Toolkit integrate with UBOS?

The Atlan AI Agent Toolkit is available on the UBOS Asset Marketplace. UBOS is a full-stack AI Agent Development Platform that helps you orchestrate AI Agents, connect them with your enterprise data, and build custom AI Agents, making it an ideal environment for deploying and managing agents built with the toolkit.

What programming language is required for using the Atlan AI Agent Toolkit?

The Atlan AI Agent Toolkit requires Python 3.11 or higher.

How can I contribute to the Atlan AI Agent Toolkit?

You can contribute by creating a new branch for your changes, implementing the changes while adhering to the MCP specification, submitting a pull request against the `main` branch, ensuring code quality with pre-commit hooks, and updating the documentation to reflect your changes.

Where can I find setup instructions for the Atlan AI Agent Toolkit?

Setup instructions can be found in the Model Context Protocol README within the Atlan AI Agent Toolkit repository.

Atlan Agent Toolkit

This repository contains a collection of tools and protocols for interacting with Atlan services for AI agents. Each component is designed to provide specific functionality and can be used independently or together.

Components

Model Context Protocol (MCP)

A protocol server that enables interaction with Atlan services through function calling. Provides tools for asset search, and retrieval using pyatlan.

Contributing Guidelines

We welcome contributions to the Atlan Agent Toolkit! Please follow these guidelines when submitting pull requests:

Create a New Branch:
- Create a new branch for your changes.
- Use a descriptive name for the branch (e.g., feature/add-new-tool).
Make Your Changes:
- Make your changes in the new branch.
- Ensure your tools are well-defined and follow the MCP specification.
Submit a Pull Request:
- Push your changes to your branch.
- Create a pull request against the main branch.
- Provide a clear description of the changes and any related issues.
- Ensure the PR passes all CI checks before requesting a review.
Code Quality:
- We use pre-commit hooks to maintain code quality.
- Install pre-commit in your local environment:
```
uv pip install pre-commit
pre-commit install
```
- Pre-commit will automatically run checks before each commit, including:
  - Code formatting with Ruff
  - Trailing whitespace removal
  - End-of-file fixing
  - YAML and JSON validation
  - Other quality checks
Environment Setup:
- This project uses UV for dependency management.
- Refer to the Model Context Protocol README for setup instructions.
- Python 3.11 or higher is required.
Documentation:
- Update documentation to reflect your changes.
- Add comments to your code where necessary.