Question 1

What is the Treasure Data MCP Server?

Accepted Answer

The Treasure Data MCP Server is a Model Context Protocol (MCP) server that enables AI models like Claude Code and Claude Desktop to interact with the Treasure Data API. It allows AI Agents to programmatically manage databases and workflows within Treasure Data.

Question 2

Is the Treasure Data MCP Server officially supported by Treasure Data Inc.?

Accepted Answer

No, this is a personal development project and is not officially affiliated with or endorsed by Treasure Data Inc. Use it at your own risk.

Question 3

What are the key features of the Treasure Data MCP Server?

Accepted Answer

Key features include database management (listing and retrieving databases and tables) and workflow project management (listing, retrieving, and downloading projects, listing files within archives, and reading specific files).

Question 4

What is MCP (Model Context Protocol)?

Accepted Answer

MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs).

Question 5

How do I authenticate with the Treasure Data MCP Server?

Accepted Answer

You need to provide a Treasure Data API key via the `TD_API_KEY` environment variable. You can also specify the Treasure Data endpoint using the `TD_ENDPOINT` environment variable (defaults to api.treasuredata.com).

Question 6

What are the software requirements for running the Treasure Data MCP Server?

Accepted Answer

The project requires Python 3.11+ and the following packages: `requests`, `pydantic`, and `mcp`. You can install the dependencies using `pip install -r requirements.txt` or `uv pip install -e .`.

Question 7

How do I set up the Treasure Data MCP Server with Claude Code?

Accepted Answer

1. Clone the repository. 2. Add the MCP server using the Claude Code CLI, specifying the absolute path to the `server.py` file and setting the necessary environment variables.

Question 8

How do I set up the Treasure Data MCP Server with Claude Desktop?

Accepted Answer

Configure the MCP server in your `claude_desktop_config.json` file, specifying the command, arguments, and environment variables needed to run the server.

Question 9

What can I do with the downloaded project archives?

Accepted Answer

You can examine the detailed project contents, including SQL queries and workflow definitions, to understand and optimize your Treasure Data workflows.

Question 10

How does the Treasure Data MCP Server integrate with the UBOS platform?

Accepted Answer

The UBOS platform provides a centralized environment for managing AI Agent components, simplifies deployment, offers a secure environment, ensures scalability and reliability, and enables multi-agent orchestration.

Question 11

Where can I find the Treasure Data MCP Server in UBOS?

Accepted Answer

The Treasure Data MCP Server is available on the UBOS Asset Marketplace.

Question 12

What are some example use cases for the Treasure Data MCP Server?

Accepted Answer

Use cases include automated data auditing, intelligent workflow orchestration, automated data pipeline management, proactive data governance, and custom AI-powered data analysis.

Question 13

What versions of Python are supported?

Accepted Answer

Python 3.11 and later are supported.

Question 14

What if I encounter issues or have questions about the Treasure Data MCP Server?

Accepted Answer

Since this is a personal project, support may be limited. However, you can review the project's documentation and code on GitHub for guidance. You can also consult the UBOS community forums for assistance.

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