Connect BigQuery to Claude Code

Let Claude run scoped reads and writes against your BigQuery data. From the terminal, inside the sessions where you already work.

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How do you connect BigQuery to Claude Code?

Claude Code reaches outside tools through MCP servers. To connect BigQuery, you add a BigQuery MCP server: a small hosted service that exposes BigQuery's data and actions over the Model Context Protocol. With a custom connector we build for you, that is one command in the terminal, then an OAuth sign-in with your own BigQuery account. No API keys pasted into config files.

claude mcp add --transport http bigquery https://your-connector-url/mcp

Then run /mcp inside a Claude Code session to sign in. Add it with --scope project and the connector is checked into the repo for your whole team.

What can Claude Code do in BigQuery once connected?

Full read-write BigQuery access lets Claude create and replace tables, run write queries, load and append rows, materialize query results into new tables, and manage datasets, all within the permissions you grant. The modeling and data preparation that used to mean hand-running SQL happen where your warehouse already lives.

Run a CREATE TABLE AS SELECT to materialize a query result into a new table
Append rows to an existing table from a query or staged data
Create or update a dataset and set its default table expiration
Run an INSERT, UPDATE, or MERGE statement against a table after you approve it
Build a scheduled-query candidate and save the SQL for your review
Replace a reporting table in place once the refreshed query validates

One connector, every Claude surface

The connector we build is a remote MCP server, which is the same standard claude.ai and Claude Desktop use. Add it once and the same BigQuery access works in Claude Code for you, in claude.ai for the rest of the team, and in Claude Desktop. One build, one set of permissions, one monthly plan covering all of them.

Build it yourself, or have it built?

If you live in the terminal, you can absolutely write your own MCP server against the BigQuery API. The protocol is open. What you take on is everything around the happy path: OAuth token refresh, hosting, monitoring, keeping up when BigQuery changes its API and when the MCP spec itself moves, and scoping write actions so an agent can never do more than you intended. We build BigQuery connectors with separated read and write tools and approval gates on destructive actions, then host and maintain them so they keep working while you work.

Frequently asked questions

Does the same BigQuery connector work in claude.ai and Claude Code?

Yes. It is one remote MCP server. Claude Code adds it with a single "claude mcp add" command; claude.ai and Claude Desktop add it as a custom connector in Settings. Each person signs in with their own BigQuery account, so access always matches what that person can already see and do.

Do I need to host or maintain anything myself?

No. The connector runs as a hosted service we operate: we handle uptime, token health, API changes on BigQuery's side, and MCP spec migrations under the monthly plan. Your side is one command in the terminal and an OAuth sign-in.

Is it safe to give a coding agent write access to BigQuery?

Write access is scoped, not blanket. Read tools and write tools are separated, destructive actions like deleting or sending are gated behind your explicit approval, and the connector can never exceed the permissions of the BigQuery account it signs in with. Revoking access is one click in BigQuery.

More on the BigQuery connector

BigQuery connector for claude.ai Snowflake + Claude Code PostgreSQL + Claude Code Databricks + Claude Code

Tell us what you run. We'll build the connector.

Pick your tool, choose what Claude should do, and get an instant scope and price. No call required.

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