BigQuery MCP Server

BigQuery MCP server enabling AI agents to interact with Google BigQuery — executing SQL queries against petabyte-scale datasets, listing datasets and tables, exploring schema, running analytical queries, and integrating BigQuery's serverless data warehouse capabilities into agent-driven analytics and data pipeline workflows.

Evaluated Mar 07, 2026 (0d ago) vcurrent
Homepage ↗ Repo ↗ Developer Tools bigquery google-cloud sql analytics mcp-server data-warehouse olap
⚙ Agent Friendliness
74
/ 100
Can an agent use this?
🔒 Security
85
/ 100
Is it safe for agents?
⚡ Reliability
78
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
72
Documentation
80
Error Messages
75
Auth Simplicity
62
Rate Limits
78

🔒 Security

TLS Enforcement
100
Auth Strength
88
Scope Granularity
82
Dep. Hygiene
75
Secret Handling
78

TLS enforced. Google Cloud IAM for BigQuery. SOC2, HIPAA, GDPR. Community MCP server. Use read-only service account. Protect service account credentials. Monitor query costs.

⚡ Reliability

Uptime/SLA
85
Version Stability
75
Breaking Changes
78
Error Recovery
72
AF Security Reliability

Best When

An agent needs to query Google BigQuery for large-scale analytics — petabyte-scale SQL queries, GCP-native data pipelines, or Google Analytics / GA4 data.

Avoid When

You're using Snowflake, Redshift, or Databricks — or if you need OLTP transactions rather than analytical queries.

Use Cases

  • Running analytical SQL queries against BigQuery datasets from data analysis agents
  • Exploring dataset and table schema from data discovery agents
  • Generating business intelligence reports from BI agents
  • Querying application telemetry and logs from observability agents
  • Building data pipeline validation queries from ETL agents
  • Analyzing large-scale event data from marketing analytics agents

Not For

  • Teams using Snowflake, Redshift, or other data warehouses (different platform)
  • Transactional OLTP workloads (use Cloud SQL or PostgreSQL instead)
  • Teams using AWS or Azure data platforms

Interface

REST API
Yes
GraphQL
No
gRPC
Yes
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: oauth2 service_account
OAuth: Yes Scopes: Yes

Google Cloud authentication via Application Default Credentials (ADC), service account JSON key, or OAuth 2.0. Requires BigQuery Data Viewer and BigQuery Job User roles minimum. Project ID required.

Pricing

Model: usage-based
Free tier: Yes
Requires CC: Yes

BigQuery free tier covers 1TB queries/month. Pay-per-query beyond that. Agents running large queries can incur significant costs — use query cost estimates. Requires GCP project with billing enabled.

Agent Metadata

Pagination
cursor
Idempotent
Full
Retry Guidance
Not documented

Known Gotchas

  • Queries cost money — agents must be aware of scan size before running large queries (use DRY RUN)
  • GCP auth setup: ADC, service account, or OAuth — different setup paths per environment
  • Project ID and dataset location (US vs EU) must match — cross-region queries not supported
  • BigQuery uses StandardSQL by default — LegacySQL is different and deprecated
  • Large query results may need pagination or export to GCS
  • Community MCP server — may not support all BigQuery features (ML, streaming inserts, etc.)

Alternatives

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Scores are editorial opinions as of 2026-03-07.

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