Pydantic AI and Box MCP
This project is a demo of how to use the Box MCP server with Pydantic AI agents. The use case is a policy analyzer.
What is Pydantic AI and Box MCP?
Pydantic AI and Box MCP is a demo project that showcases how to utilize the Box MCP server in conjunction with Pydantic AI agents for policy analysis.
How to use Pydantic AI and Box MCP?
To use this project, you need to set up a local instance of the Box MCP server, configure it with your Box platform app, and then run the demo by executing the provided Python scripts.
Key features of Pydantic AI and Box MCP?
- Integration of Pydantic AI agents with Box MCP server.
- Policy analysis capabilities using secure content from Box.
- Easy setup and execution through command line instructions.
Use cases of Pydantic AI and Box MCP?
- Analyzing company policies for compliance.
- Automating policy review processes.
- Enhancing AI capabilities with secure content management.
FAQ from Pydantic AI and Box MCP?
- What do I need to run this project?
You need a local copy of the Box MCP server and the necessary Python libraries installed.
- Is there any cost associated with using Box MCP?
The project is a demo and does not specify costs, but using Box services may involve fees.
- Can I modify the code for my own use?
Yes, you can modify the code as needed for your specific use cases.
Pydantic AI and Box MCP
This project is a demo showing how to use the Box MCP server to augment Pydantic AI agents with secure content in Box.
To run this, you will need a local copy of our MCP server. Follow the instructions there to set up your Box platform app, register it with your Box instance, and configure the server.
The only thing you'll need to do in this project is update the following code to point to your local directory:
async with MCPServerStdio(
command='uv',
args=[
'--directory',
'/Users/shurrey/local/mcp-server-box',
'run',
'src/mcp_server_box.py'
]
) as local_server:
Once you have those steps done, navigate to this project at the commandline and set up your virtual environment:
uv venv
Then install the prerequisites libraries.
uv pip install -r pyproject.toml
Now you can run the demo.
uv run policy_analyzer.py