
MCP Toolbox for Databases (BigQuery)
OfficialGoogle's official MCP server with prebuilt BigQuery tools, querying datasets via Application Default Credentials.
Add to your client
Copy the config for your MCP client and paste it into its config file.
brew install mcp-toolbox && toolbox --prebuilt bigquery --stdioPaste into ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"mcp-toolbox-for-databases-bigquery": {
"command": "/absolute/path/to/toolbox",
"args": [
"--prebuilt",
"bigquery",
"--stdio"
],
"env": {
"BIGQUERY_PROJECT": "<your-gcp-project-id>"
}
}
}
}Before you start
- The toolbox binary (download from GitHub releases and `chmod +x`), or run via container/source; MCP Toolbox v0.7.0 or later for the full BigQuery toolset
- A Google Cloud project with the BigQuery API enabled
- Application Default Credentials configured locally (e.g. `gcloud auth application-default login`) or a service account key
- IAM roles on the project/dataset such as BigQuery User and BigQuery Data Viewer (read), plus Job User to run queries
- An MCP-capable client (Claude Desktop, Cursor, Gemini/ADK, etc.)
About MCP Toolbox for Databases (BigQuery)
MCP Toolbox for Databases is Google's open-source MCP server (the project formerly known as GenAI Toolbox) that connects AI agents, IDEs, and apps to enterprise databases. It ships a single Go binary that can serve both prebuilt, generic database tools and your own custom tools defined in a tools.yaml file. BigQuery is one of its first-class supported sources.
For BigQuery specifically, the toolbox exposes a set of prebuilt tools so an agent can discover and query data without you hand-writing INFORMATION_SCHEMA logic: it can list datasets and tables, fetch dataset/table metadata, run SQL, search the data catalog in natural language, forecast time series, run contribution (key-driver) analysis, and answer conversational analytics questions. A typical agent flow is list datasets → list tables → get table info → execute SQL.
Authentication uses Google Application Default Credentials (ADC), so the server runs as your gcloud identity or a service account with the right BigQuery IAM roles. It also offers production niceties like OpenTelemetry observability and connection management, and integrates with Google's Agent Development Kit (ADK) as well as any MCP client.
Tools & capabilities (10)
bigquery-execute-sqlRun an arbitrary SQL statement against BigQuery and return results
bigquery-sqlRun a parameterized/templated SQL query defined as a tool
bigquery-list-dataset-idsList dataset IDs available in a project
bigquery-get-dataset-infoGet metadata for a given BigQuery dataset
bigquery-list-table-idsReturn the table IDs in a given dataset
bigquery-get-table-infoGet schema and metadata for a given table
bigquery-search-catalogFind tables using a natural-language search over the data catalog
bigquery-forecastForecast time-series data using BigQuery ML forecasting
bigquery-analyze-contributionRun contribution (key-driver) analysis to explain metric changes
bigquery-conversational-analyticsAnswer complex natural-language questions about table contents (ask-data-insights)
When to use it
- Use it when you want an agent to explore an unfamiliar BigQuery project by listing datasets/tables and reading schemas before writing SQL
- Use it when you need a read-only analytics assistant over your warehouse with proper IAM scoping
- Use it when you want time-series forecasting or contribution analysis driven from natural language
- Use it when you'd rather configure tools declaratively in tools.yaml than build a bespoke MCP server
- Use it when you need production features like ADC auth and OpenTelemetry tracing for an agent-to-DB bridge
- Use it when you want the same toolbox to also reach AlloyDB, Cloud SQL, Spanner, or Postgres/MySQL alongside BigQuery
Quick setup
- 1Download the toolbox binary from GitHub releases (or use the container image) and make it executable
- 2Enable the BigQuery API and run `gcloud auth application-default login` to set up ADC
- 3Use the prebuilt BigQuery toolset (or write a tools.yaml with a bigquery source and the tools you want)
- 4Start the toolbox pointing at BigQuery, then register it in your MCP client as a stdio command
- 5Restart the client and confirm the BigQuery tools appear
- 6Verify by asking the agent to list dataset IDs and then run a simple SELECT
Security notes
Authentication relies on your local gcloud Application Default Credentials, so the server inherits whatever BigQuery permissions that identity has; use a least-privilege account. The command path must point at the toolbox binary you installed, so verify its absolute path.
MCP Toolbox for Databases (BigQuery) FAQ
How does authentication work?
It uses Google Application Default Credentials (ADC). Run `gcloud auth application-default login` for local dev, or attach a service account with the right BigQuery IAM roles.
Can I make it read-only?
Yes. Scope the credential's IAM to read roles (e.g. BigQuery Data Viewer / Job User) and expose only the read/metadata tools in your tools.yaml to enforce a read-only production pattern.
Is this the same as 'GenAI Toolbox'?
Yes. MCP Toolbox for Databases is the renamed GenAI Toolbox, maintained by Google under the googleapis org, and works with Google's ADK as well as standard MCP clients.
Which databases besides BigQuery are supported?
It supports AlloyDB, Cloud SQL (PostgreSQL/MySQL/SQL Server), Spanner, Firestore, self-managed PostgreSQL/MySQL, and more, in addition to BigQuery.
What version do I need for the full BigQuery tools?
Use MCP Toolbox v0.7.0 or later to get the complete prebuilt BigQuery toolset including forecast, contribution analysis, and conversational analytics.
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