mcp-server-google-bigquery

Provides an MCP server that connects an agent to Google BigQuery so the agent can perform BigQuery operations (e.g., query execution and related data access) via MCP tool calls. The package name indicates BigQuery-specific MCP functionality.

Evaluated Apr 04, 2026 (17d ago)

Homepage ↗ Repo ↗ Ai Ml mcp bigquery google-cloud data-analytics ai-agents sql

⚙ Agent Friendliness

/ 100

Can an agent use this?

🔒 Security

/ 100

Is it safe for agents?

⚡ Reliability

/ 100

Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality

Documentation

Error Messages

Auth Simplicity

Rate Limits

🔒 Security

TLS Enforcement

Auth Strength

Scope Granularity

Dep. Hygiene

Secret Handling

TLS support is not explicitly confirmed in the provided content. BigQuery security typically depends on how credentials are supplied and how query execution is authorized/filtered; without verified documentation, secret handling, least-privilege scopes, and query safety controls cannot be fully assessed.

⚡ Reliability

Uptime/SLA

Version Stability

Breaking Changes

Error Recovery

Use Cases

• Agent-driven analysis over BigQuery datasets using natural language converted into SQL/actions
• Automated reporting and ad-hoc analytics workflows that read from BigQuery
• Operational tasks that require querying BigQuery and returning results to an LLM/agent

Not For

• Direct end-user dashboards or interactive BI tools
• Workloads requiring strict data exfiltration controls without additional governance
• Use cases that need a REST/GraphQL/SDK-only integration without MCP support

Interface

REST API

GraphQL

gRPC

MCP Server

Yes

SDK

Webhooks

Authentication

OAuth: No Scopes: No

Authentication requirements are not provided in the prompt content. BigQuery integrations typically require Google credentials (e.g., service account / OAuth), but the exact method and scope model for this MCP server cannot be confirmed from the information available.

Pricing

Free tier: No

Requires CC: No

No pricing information is provided for the package itself. BigQuery usage may incur Google Cloud costs depending on queries and data processed, but this cannot be confirmed from the provided content.

Agent Metadata

Pagination

none

Idempotent

False

Retry Guidance

Not documented

Known Gotchas

⚠ BigQuery query execution can be expensive and slow if the agent generates unbounded queries; guardrails/quotas are important.
⚠ LLMs may produce invalid SQL dialect/fields; expect iterative correction based on error output.
⚠ Large result sets may exceed typical agent context limits; pagination/limits may be needed if supported.
⚠ Credential scope/misconfiguration is a common failure mode for Google Cloud integrations.

Alternatives

Using BigQuery directly via Google Cloud APIs/SDKs (e.g., Python/Java/Node) Using a custom integration that wraps BigQuery API with your own authorization and query policy layer Other MCP servers or agent-tool frameworks that already support BigQuery

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Scores are editorial opinions as of 2026-04-04.