BigQuery Data Platform MCP server

BigQuery MCP

A read-only Model Context Protocol server over Google BigQuery. It lets an AI client (Claude Code, Claude Desktop, …) answer plain-language data questions by discovering schema and running SELECT queries.

The AI does the natural-language → SQL translation; this server just safely executes against BigQuery under your own Google credentials.

• Docs: https://debilla.github.io/bigquery-mcp/
• Repo: https://github.com/deBilla/bigquery-mcp
• PyPI: data-platform-mcp
• MCP registry: mcp-name: io.github.deBilla/data-platform-mcp

Tools exposed

Only run_query costs anything, so the discovery tools are the ones to spend first. Two of them exist to prevent specific, repeated mistakes:

column names. A table with a partitiondate column may not be partitioned — in which case no WHERE clause reduces the scan and every query reads the whole table. The response flags this explicitly when the table is large.

• gettable_schema reports partitioning from table metadata, never from

being dropped. Those return stale data rather than an error, which is the failure mode nobody notices.

• checktablefreshness finds tables that stopped being written to without

tools say what writes a table; this says who reads it, which is the question before a schema change. It is also the one discovery tool that is not free: it opens every asset it considers, spending Dataform read quota, so it is capped and reports how much of the project it actually covered. A result is evidence about the assets scanned, never proof that nothing else uses the table — assets it could not read are listed separately rather than counted as misses.

• findcodeassetsusingtable answers the other half. The scheduled-query

query that was disabled or is failing, and that lives in a different API (BigQuery Data Transfer) needing roles/bigquerydatatransfer.viewer. Without that role the two tools return an error naming it and everything else works normally. Most scheduled queries declare no destination because they write with DDL, so the target is read out of the SQL and reported as writestofrom_sql — a heuristic, labelled as one.

• listscheduledqueries says why. A stale table is usually a scheduled

BigQuery Studio notebooks and saved queries

Shortened. The full README is on GitHub.