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td-mcp-server
A Model Context Protocol (MCP) server that provides Treasure Data API integration for Claude Code and Claude Desktop.
DISCLAIMER: This is a personal development project and is not affiliated with, endorsed by, or related to Treasure Data Inc. in any way. This software is provided "as is" without warranty of any kind, and should be used at your own risk. The author is not responsible for any consequences resulting from the use of this software.
For comprehensive Treasure Data documentation and tools:
This MCP server provides a comprehensive set of tools for interacting with Treasure Data, organized by functionality. Currently offering 23 tools across 6 categories:
td_list_databases
td_list_databases(verbose=False, limit=30, offset=0, all_results=False)
verbose: If True, return full details; if False, return only names (default)limit: Maximum number of databases to retrieve (defaults to 30)offset: Index to start retrieving from (defaults to 0)all_results: If True, retrieves all databases ignoring limit and offset# Get only database names (default, first 30 databases)
td_list_databases
# Get full database details
td_list_databases verbose=True
# Pagination options
td_list_databases limit=10 offset=20
# Get all databases regardless of the number
td_list_databases all_results=True
td_get_database
td_get_database(database_name)
database_name: The name of the database to retrieve information for# Get information about a specific database
td_get_database database_name=my_database_name
td_list_tables
td_list_tables(database_name, verbose=False, limit=30, offset=0, all_results=False)
database_name: The name of the database to retrieve tables fromverbose: If True, return full details; if False, return only names (default)limit: Maximum number of tables to retrieve (defaults to 30)offset: Index to start retrieving from (defaults to 0)all_results: If True, retrieves all tables ignoring limit and offset# Get only table names in a database (default, first 30 tables)
td_list_tables database_name=my_database_name
# Get detailed information about tables in a database
td_list_tables database_name=my_database_name verbose=True
# Pagination options
td_list_tables database_name=my_database_name limit=10 offset=20
# Get all tables in a database
td_list_tables database_name=my_database_name all_results=True
td_list_projects
td_list_projects(verbose=False, limit=30, offset=0, all_results=False, include_system=False)
verbose: If True, return full details; if False, return only names and IDs (default)limit: Maximum number of projects to retrieve (defaults to 30)offset: Index to start retrieving from (defaults to 0)all_results: If True, retrieves all projects ignoring limit and offsetinclude_system: If True, include system-generated projects (with "sys" metadata); defaults to False# Get basic project info (default, first 30 projects)
td_list_projects
# Get detailed project information
td_list_projects verbose=True
# Pagination options
td_list_projects limit=10 offset=20
# Get all projects regardless of the number
td_list_projects all_results=True
# Include system-generated projects
td_list_projects include_system=True
td_get_project
td_get_project(project_id)
project_id: The ID of the workflow project to retrieve information for# Get information about a specific project
td_get_project project_id=123456
td_download_project_archive
td_download_project_archive(project_id)
project_id: The ID of the workflow project to download# Download a project's archive
td_download_project_archive project_id=123456
td_list_project_files
td_list_project_files(archive_path)
archive_path: The path to the downloaded project archive (.tar.gz file)# List files in a downloaded project archive
td_list_project_files archive_path=/tmp/td_project_123/project_123456.tar.gz
td_read_project_file
td_read_project_file(archive_path, file_path)
archive_path: The path to the downloaded project archive (.tar.gz file)file_path: The path of the file within the archive to read# Read a specific file from a project archive
td_read_project_file archive_path=/tmp/td_project_123/project_123456.tar.gz file_path=workflow.dig
td_list_workflows
td_list_workflows(verbose=False, count=100, include_system=False, status_filter=None)
verbose: If True, return full details including sessions; if False, return summary (default)count: Maximum number of workflows to retrieve (defaults to 100, max 12000)include_system: If True, include system-generated workflows (with "sys" metadata)status_filter: Filter workflows by their last session status ('success', 'error', 'running', None for all)# Get workflow summary (default)
td_list_workflows
# Get full workflow details with recent sessions
td_list_workflows verbose=True
# Get only failed workflows
td_list_workflows status_filter=error
# Get successful workflows including system workflows
td_list_workflows status_filter=success include_system=True
# Get more workflows (up to 12000)
td_list_workflows count=500
td_smart_search(query, search_scope="all", search_mode="fuzzy", active_only=True, min_relevance=0.7)
query: Search term or phrasesearch_scope: Where to search - "projects", "workflows", "tables", "all" (default: "all")search_mode: Search algorithm - "exact", "fuzzy", "semantic" (default: "fuzzy")active_only: Filter to only active/non-deleted resources (default: True)min_relevance: Minimum relevance score (0-1) for results (default: 0.7)# Search everywhere with fuzzy matching
td_smart_search query="customer clustering"
# Exact search for projects only
td_smart_search query="my_project" search_scope=projects search_mode=exact
# Semantic search for workflows
td_smart_search query="recommendation engine" search_scope=workflows search_mode=semantic
# Lower relevance threshold for broader results
td_smart_search query="sales" min_relevance=0.5
td_find_project(search_term, exact_match=False)
search_term: Project name or partial name to search forexact_match: If True, only return exact matches (default: False)# Find projects containing "cluster"
td_find_project search_term=cluster
# Find exact project name
td_find_project search_term="customer_analytics" exact_match=True
td_find_workflow(search_term, project_name=None, exact_match=False, status_filter=None)
search_term: Workflow name or partial name to search forproject_name: Optional project name to filter byexact_match: If True, only return exact matches (default: False)status_filter: Filter by status ('success', 'error', 'running', None)# Find workflows containing "scoring"
td_find_workflow search_term=scoring
# Find workflows in specific project
td_find_workflow search_term=daily project_name=my_project
# Find failed workflows with exact name
td_find_workflow search_term="ore_heaven_scoring" exact_match=True status_filter=error
td_get_project_by_name(project_name)
project_name: Exact project name# Get project details by name
td_get_project_by_name project_name="customer_analytics"
td_analyze_url(url)
url: Console URL to analyzehttps://console.us01.treasuredata.com/app/workflows/12345678/infohttps://console.us01.treasuredata.com/app/projects/123456https://console.us01.treasuredata.com/app/jobs/123456# Analyze a workflow URL
td_analyze_url url="https://console.us01.treasuredata.com/app/workflows/12345678/info"
td_get_workflow(workflow_id)
workflow_id: Numeric workflow ID# Get workflow by ID
td_get_workflow workflow_id=12345678
td_explore_project(identifier, analysis_depth="detailed", focus_areas=None)
identifier: Project name, ID, or search termanalysis_depth: Level of analysis - "overview", "detailed", or "deep" (default: "detailed")focus_areas: Specific aspects to analyze - ["code", "data_flow", "performance", "errors"] (default: ["code", "data_flow"])# Get detailed project analysis
td_explore_project identifier="my_project"
# Deep analysis focusing on performance
td_explore_project identifier="analytics_workflow" analysis_depth=deep focus_areas=["performance", "errors"]
# Quick overview
td_explore_project identifier=1664373 analysis_depth=overview
td_diagnose_workflow(workflow_identifier, time_window="30d", diagnostic_level="basic")
workflow_identifier: Workflow name, ID, or partial matchtime_window: Time period to analyze (e.g., "30d", "7d", "24h") (default: "30d")diagnostic_level: "basic" for quick check, "comprehensive" for deep analysis (default: "basic")# Basic health check for last 30 days
td_diagnose_workflow workflow_identifier="ore_heaven_scoring"
# Comprehensive diagnosis for last week
td_diagnose_workflow workflow_identifier=12345678 time_window=7d diagnostic_level=comprehensive
# Quick check for recent issues
td_diagnose_workflow workflow_identifier="daily_batch" time_window=24h
td_trace_data_lineage(table_or_project, direction="both", max_depth=3)
table_or_project: Table name (format: "database.table") or project name/IDdirection: "upstream" (sources), "downstream" (consumers), or "both" (default: "both")max_depth: Maximum levels to trace (default: 3)# Trace table dependencies
td_trace_data_lineage table_or_project="production.customer_segments"
# Find upstream sources only
td_trace_data_lineage table_or_project="analytics.recommendations" direction=upstream
# Trace project data flow
td_trace_data_lineage table_or_project="my_project" max_depth=5
td_get_session(session_id)
session_id: The ID of the session to retrieve# Get session details
td_get_session session_id=123456789
td_list_sessions(workflow_id=None, count=20)
workflow_id: Optional workflow ID to filter sessionscount: Number of recent sessions to retrieve (default 20)# List recent sessions across all workflows
td_list_sessions
# List sessions for a specific workflow
td_list_sessions workflow_id=12345678 count=50
td_get_attempt(attempt_id)
attempt_id: The ID of the attempt to retrieve# Get attempt details
td_get_attempt attempt_id=987654321
td_get_attempt_tasks(attempt_id)
attempt_id: The ID of the attempt# Get task breakdown for an attempt
td_get_attempt_tasks attempt_id=987654321
td_analyze_execution(url_or_id)
url_or_id: Console URL, session ID, or attempt ID# Analyze from console URL
td_analyze_execution url_or_id="https://console.us01.treasuredata.com/app/sessions/123456"
# Analyze from session ID
td_analyze_execution url_or_id=123456789
# Analyze from attempt ID
td_analyze_execution url_or_id=987654321
To test the MCP tools with real API calls:
# Set your API key (required)
export TD_API_KEY="your-api-key"
# Run integration tests
python test_mcp_integration.py
The integration test script (test_mcp_integration.py) safely tests all tools by:
Important: Never commit files containing:
This MCP server requires a Treasure Data API key for authentication, which should be provided 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).
Clone the repository
git clone https://github.com/knishioka/td-mcp-server.git
cd td-mcp-server
Install dependencies
# Using pip
pip install -r requirements.txt
# Or using uv (recommended)
uv pip install -e .
Set up environment variables and run
# Set your API key
export TD_API_KEY="your-api-key"
export TD_ENDPOINT="api.treasuredata.com" # Optional, defaults to US region
# Run the MCP server
mcp run td_mcp_server/server.py
Configure this 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"
}
}
}
}
This project requires Python 3.11+ and the following dependencies:
requests>=2.28.0 - HTTP client for API requestspydantic>=2.0.0 - Data validation and serializationmcp[cli]>=1.8.1 - Model Context Protocol frameworkInstall the dependencies:
# Using pip
pip install -r requirements.txt
# Using uv (recommended for development)
uv pip install -e .
You can run the MCP server directly:
# Set your API key
export TD_API_KEY="your-api-key"
# For US region (default)
export TD_ENDPOINT="api.treasuredata.com"
# For Japan region
# export TD_ENDPOINT="api.treasuredata.co.jp"
# Run with MCP CLI
mcp run td_mcp_server/server.py
# Run all tests
pytest
# Run tests with coverage report
pytest --cov=td_mcp_server
# Run tests for a specific module
pytest tests/unit/test_api.py
# Run linting with Ruff
uv run ruff check td_mcp_server tests
# Format code with Ruff
uv run ruff format td_mcp_server tests
# Run pre-commit hooks on all files
uv run pre-commit run --all-files
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