Bigquery Mcp
Query and explore Google BigQuery datasets from your agent when reviewing product or marketing metrics.
Overview
io.github.SnowLeopard-AI/bigquery-mcp is a Grow-phase MCP server that provides AI agents managed access to query Google BigQuery data.
What is this MCP server?
- SnowLeopardAI-managed MCP server exposing Google BigQuery to agents.
- PyPI package sl-bigquery-mcp (published 0.1.9) with stdio transport.
- Lets coding agents run warehouse reads without hand-writing every SQL file in the IDE.
- Fits solo builders who centralize event or billing data in BigQuery.
- Repository and packaging aligned with the official MCP server schema (server metadata 0.1.1).
- PyPI package identifier sl-bigquery-mcp version 0.1.9
- Server registry version 0.1.1 in MCP metadata
- stdio transport; repository github.com/SnowLeopard-AI/bigquery-mcp
Community signal: 10 GitHub stars.
What problem does it solve?
Jumping between BigQuery console and your agent breaks iterative metric investigations when you just need quick warehouse answers.
Who is it for?
Indie builders with data already in BigQuery who want agent-assisted SQL and exploration during analytics reviews.
Skip if: Teams without BigQuery, greenfield projects with no warehouse yet, or environments that block cloud credentials in local MCP processes.
What do I get? / Deliverables
After setup, your agent can query BigQuery through MCP tools so growth and product questions get answered in one conversational workflow.
- Agent-executable BigQuery reads and explorations
- Faster ad-hoc answers for growth and product metrics
- Documented MCP server wiring alongside other data tools
Recommended MCP Servers
Journey fit
Warehouse queries for funnel, revenue, and usage metrics most often support the Grow phase after you have data flowing from a shipped product. Analytics is the canonical placement for read-oriented BigQuery access used in weekly metric reviews and ad-hoc growth investigations.
How it compares
BigQuery data-access MCP, not an ETL pipeline or dashboard builder skill.
Common Questions / FAQ
Who is io.github.SnowLeopard-AI/bigquery-mcp for?
Solo builders and small teams using Google BigQuery for product or growth data who want Claude Code, Cursor, or similar agents to query via MCP.
When should I use io.github.SnowLeopard-AI/bigquery-mcp?
Use it in Grow analytics work when you need fast, agent-driven queries against existing BigQuery tables without exporting CSVs manually.
How do I add io.github.SnowLeopard-AI/bigquery-mcp to my agent?
Install sl-bigquery-mcp from PyPI, configure GCP/BigQuery authentication per SnowLeopard-AI/bigquery-mcp docs, and add the stdio MCP server entry in your client.