
Google BigQuery
BetaQuery and explore BigQuery data warehouses. Discover datasets/tables, inspect schema, and run read-only SQL — governed by Cloud IAM.
- Analytics
- Data Warehouse
- SQL
- Authentication
- OAuth 2.0
- Hosting
- Vendor-hosted endpoint
- Required scopes
- 1
- Data actions
- Read and write
How it works
Every agent request passes through Ferentin policy before it reaches Google BigQuery.
Ferentin's Google BigQuery MCP server connects agents to a project's datasets through OAuth2 + Cloud IAM, with tools for dataset/table discovery, schema inspection, and read-only SQL execution. execute_sql is SELECT-only on the managed endpoint; access is scoped by the signing-in identity's IAM grants.
- AI agentAsks for something
- Ferentin policies
- OAuth 2.0 consent
- Cloud iam authorization
- No API keys
- Audit logging
- Google BigQuery MCP serverAuthorized connection
- Governed resultMasked, logged, returned
What agents can do
6 tools · you choose which ones agents may callSearch and browse what exists, without opening the content itself.
- list_dataset_ids
- list_table_ids
Permissions requested
The OAuth 2.0 scopes Google BigQuery asks you to approve when you connect.
| Scope | Access |
|---|---|
| https://www.googleapis.com/auth/bigquery | Not rated |
Before you connect
- Google does not support Dynamic Client Registration (DCR) — each tenant must create its own OAuth client in Google Cloud Console.
- Authentication is OAuth 2.0 + Google Cloud IAM. API keys are not accepted; access is enforced by the signing-in identity's IAM roles.
- Use access_type=offline to receive a refresh token for long-lived access.
- On the fully-managed server, execute_sql accepts SELECT statements only.
3 more technical notes
- Query results are limited to 3,000 rows and 3 minutes of processing time.
- The scope https://www.googleapis.com/auth/bigquery is required; cloud-platform works as a superset.
- Google Drive-backed external tables cannot be queried through this server.
About Google BigQuery
BigQuery is Google Cloud's serverless, petabyte-scale data warehouse for analytics over structured and semi-structured data using GoogleSQL.
Frequently asked about Google BigQuery
- What can AI agents do with Google BigQuery through Ferentin?
- Ferentin exposes 6 Google BigQuery MCP tools to your AI agents, grouped as Discover (2 tools), Access (2 tools) and Manage (2 tools). Every call is checked against your Ferentin policies before it reaches Google BigQuery.
- How is Google BigQuery access secured?
- Requests through the Google BigQuery integration are covered by OAuth 2.0 consent, cloud iam authorization, no API keys and audit logging. These controls are applied by Ferentin, not by Google BigQuery, so they hold across every connected agent.
- What permissions does the Google BigQuery integration require?
- The Google BigQuery integration requests 1 OAuth 2.0 scope: https://www.googleapis.com/auth/bigquery
- How do I connect Google BigQuery to Ferentin?
- Open the Ferentin admin console, add Google BigQuery as a new connection and authenticate with OAuth 2.0. You then choose which permissions and which tools your agents may use, and the connection goes live for everyone covered by your policies.
- Is the Google BigQuery integration generally available?
- The Google BigQuery integration is currently beta on Ferentin.
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