bigquery-mcp-data-agent
Enables AI agents to analyze BigQuery datasets through MCP, using tools to inspect datasets and execute read-only SQL queries.
README
BigQuery MCP Data Agent
An AI-powered data analysis agent built with Google's Agent Development Kit (ADK), Gemini, BigQuery MCP Server, and Cloud Run.
Overview
This project demonstrates how an AI agent can connect to structured data in BigQuery through the Model Context Protocol (MCP).
The agent analyzes the NYC Citi Bike dataset and can answer analytical questions by inspecting the dataset, generating SQL queries, and retrieving data from BigQuery.
Technologies
- Google Agent Development Kit (ADK)
- Gemini
- BigQuery
- BigQuery MCP Server
- Model Context Protocol (MCP)
- Google Cloud Run
- Python
Dataset
The agent works with the public NYC Citi Bike dataset:
bigquery-public-data.new_york_citibike
The dataset contains information about Citi Bike trips and stations in New York City.
How It Works
- The user asks a question about the Citi Bike data.
- Gemini analyzes the question.
- The ADK agent uses BigQuery MCP tools to inspect the dataset.
- The agent generates and executes read-only SQL queries.
- BigQuery returns the requested data.
- Gemini analyzes the results and provides an answer.
MCP Tools Used
The agent uses the following BigQuery MCP tools:
get_dataset_infolist_table_idsget_table_infoexecute_sql_readonly
Example Question
We have budget for 3 coffee trucks.
We want to find the best city bike stations to place our coffee trucks.
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