UBOS Asset Marketplace: Treasure Data MCP Server - Unleash the Power of Data-Driven AI Agents

In the rapidly evolving landscape of AI, the ability for AI Agents to access and process real-world data is paramount. The UBOS platform recognizes this need and is committed to providing comprehensive tools and integrations that empower developers to build smarter, more effective AI Agents. One such integration is the Treasure Data MCP (Model Context Protocol) Server, now available on the UBOS Asset Marketplace.

This document offers an in-depth exploration of the Treasure Data MCP Server, its capabilities, its use cases, and how it seamlessly integrates with the UBOS platform to supercharge your AI Agent development.

What is the Treasure Data MCP Server?

The Treasure Data MCP Server acts as a crucial bridge, facilitating communication between AI models, specifically Claude Code and Claude Desktop, and the Treasure Data platform. Treasure Data is a leading customer data platform (CDP) that unifies data from various sources to create a single, comprehensive view of your customers. By leveraging the MCP server, AI Agents can programmatically interact with Treasure Data, accessing valuable data for informed decision-making and enhanced task automation.

The MCP, or Model Context Protocol, is an open standard defining how applications provide context to Large Language Models (LLMs). This server, compliant with the MCP, offers specific tools tailored to the Treasure Data API. It enables AI Agents to programmatically manage databases and workflows within Treasure Data, providing an efficient, automated, and data-driven approach.

Disclaimer: It is important to note that this MCP server is an independent development project and is not officially affiliated with or endorsed by Treasure Data Inc. Users should exercise caution and utilize the software at their own risk.

Key Features of the Treasure Data MCP Server

The Treasure Data MCP Server offers a rich set of functionalities designed to streamline data access and workflow management. These features include:

• Database Management:
  • td_list_databases: Retrieve a list of databases within your Treasure Data account. This tool supports pagination, enabling you to efficiently manage large numbers of databases. You can choose to retrieve only database names or detailed information for each database.
  • td_get_database: Obtain comprehensive information about a specific database, providing insights into its structure and contents.
  • td_list_tables: List all tables within a specified Treasure Data database, again with pagination support. Similar to td_list_databases, you can opt for basic table names or detailed table information.
• Workflow Project Management:
  • td_list_projects: Enumerate workflow projects in your Treasure Data account, supporting pagination and filtering options. You can choose to include system-generated projects and retrieve either basic project information or detailed metadata.
  • td_get_project: Access detailed information about a particular workflow project, providing a high-level overview of the project’s configuration.
  • td_download_project_archive: Download a project’s archive file (tar.gz), allowing for in-depth examination of the project’s contents, including SQL queries and workflow definitions. This is crucial for understanding the intricate details of complex workflows.
  • td_list_project_files: List all files contained within a downloaded project archive, providing a directory structure of the project’s components.
  • td_read_project_file: Read the contents of a specific file from a project archive, enabling you to programmatically access and analyze individual files within the workflow project.

Use Cases: How the Treasure Data MCP Server Empowers AI Agents

The Treasure Data MCP Server unlocks a multitude of use cases for AI Agents within the UBOS ecosystem. Here are some illustrative examples:

1. Automated Data Auditing and Monitoring:

   • AI Agents can be programmed to periodically list databases and tables, checking for inconsistencies, anomalies, or outdated schemas.
   • By comparing current database structures with historical data, Agents can identify potential data quality issues and trigger alerts.

2. Intelligent Workflow Orchestration:

   • AI Agents can analyze workflow project definitions (SQL queries, workflow configurations) to optimize execution paths and resource allocation.
   • Based on data dependencies and performance metrics, Agents can dynamically adjust workflow parameters to minimize processing time and costs.

3. Automated Data Pipeline Management:

   • AI Agents can monitor data ingestion pipelines, identifying bottlenecks and potential failure points.
   • By analyzing project archives, Agents can automatically update data transformation scripts and ensure data consistency across the platform.

4. Proactive Data Governance and Compliance:

   • AI Agents can scan database metadata and workflow definitions to identify sensitive data and ensure compliance with data governance policies.
   • Agents can automatically generate reports on data usage and access patterns, facilitating audit trails and regulatory compliance.

5. Custom AI-Powered Data Analysis:

   • AI Agents can leverage the MCP server to access and analyze data stored in Treasure Data, performing tasks such as customer segmentation, predictive analytics, and anomaly detection.
   • These insights can then be used to personalize customer experiences, optimize marketing campaigns, and improve business decision-making.

Integration with the UBOS Platform

The Treasure Data MCP Server seamlessly integrates with the UBOS platform, providing a unified environment for AI Agent development and deployment. UBOS offers several key advantages:

• Centralized Asset Management: The UBOS Asset Marketplace provides a central repository for discovering, deploying, and managing AI Agent components, including the Treasure Data MCP Server.
• Simplified Deployment: UBOS streamlines the deployment process, allowing you to easily configure and launch the MCP server with minimal manual configuration.
• Secure Environment: UBOS provides a secure and isolated environment for running AI Agents, protecting your sensitive data and ensuring compliance with security policies.
• Scalability and Reliability: UBOS is designed for scalability, allowing you to easily scale your AI Agent deployments to meet the demands of your business. The platform also offers high availability and reliability, ensuring that your Agents are always running.
• Multi-Agent Orchestration: UBOS excels at orchestrating complex multi-agent systems. You can easily combine the Treasure Data MCP Server with other AI Agents and tools to create sophisticated solutions for a wide range of business problems.
• Custom AI Agent Building with LLM and Multi-Agent Systems: Build tailored AI Agents using your preferred LLMs. UBOS supports multi-agent systems allowing to create complex solutions.
• Enterprise Data Connectivity: Connect AI Agents to your existing enterprise data sources. UBOS provides secure and reliable data connectivity.

Setting up the Treasure Data MCP Server

To utilize the Treasure Data MCP Server, you need to configure it with your Treasure Data API key and endpoint. This can be done through environment variables, as detailed in the original documentation. Specifically, the TD_API_KEY variable must be set to your API key, and the TD_ENDPOINT variable can be set to your Treasure Data endpoint (defaults to api.treasuredata.com).

When deploying the MCP server within the UBOS platform, you can configure these environment variables through the UBOS interface, ensuring secure storage and easy management.

Setup Instructions with Claude Code

1. Clone the Repository:

   bash git clone https://github.com/knishioka/td-mcp-server.git

2. Add the MCP Server using the Claude Code CLI:

   bash

   Navigate to your project directory

   cd your-project-directory

   Add the MCP server (use absolute path to server.py)

   claude mcp add td -e TD_API_KEY=${TD_API_KEY} -e TD_ENDPOINT=api.treasuredata.com – mcp run /absolute/path/to/td-mcp-server/td_mcp_server/server.py

Setup Instructions with Claude Desktop

Configure the MCP server for use with Claude Desktop by editing your configuration file (claude_desktop_config.json):

{ “mcpServers”: { “td”: { “command”: “uv”, “args”: [ “–directory”, “/absolute/path/to/td-mcp-server”, “run”, “td_mcp_server/server.py” ], “env”: { “TD_API_KEY”: “YOUR_API_KEY”, “TD_ENDPOINT”: “api.treasuredata.com” } } } }

Installation and Requirements

The project requires Python 3.11+ and the following packages:

• requests
• pydantic
• mcp

Install the dependencies with pip:

bash pip install -r requirements.txt

Or with uv:

bash uv pip install -e .

Conclusion: Empowering the Future of AI with Data

The Treasure Data MCP Server is a powerful tool that bridges the gap between AI models and real-world data. By leveraging this integration within the UBOS platform, developers can create smarter, more data-driven AI Agents that deliver tangible business value. Whether you’re automating data auditing, optimizing workflows, or building custom AI-powered analytics solutions, the Treasure Data MCP Server is an invaluable asset in your AI arsenal.

As AI continues to evolve, the ability to access and process data will become even more critical. The UBOS platform is committed to providing the tools and integrations necessary to empower developers to build the next generation of AI solutions. Explore the UBOS Asset Marketplace today and discover how the Treasure Data MCP Server can transform your AI Agent development efforts.