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MCP Server
Official Remote

BigQuery MCP Server: Governed AI Access

BigQuery's MCP server includes 6 different actions available to any connected model or AI agent. When registered with Barndoor, you can ensure centralized governance, visibility, and control across every AI agent your team uses.

Tools6

CapabilitiesRead, Update

TypeOfficial Remote

What can AI agents do with the BigQuery MCP server?

Tools Available

list_dataset_ids
read
List BigQuery dataset IDs in a Google Cloud project.
get_dataset_info
read
Get metadata information about a BigQuery dataset.
list_table_ids
read
List table ids in a BigQuery dataset.
get_table_info
read
Get metadata information about a BigQuery table.
execute_sql_readonly
read
Run a read-only SQL query in the project and return the result.
execute_sql
update
Run a SQL query in the project, supporting SELECT, INSERT, UPDATE, DELETE, CREATE, and AI/ML functions.
See full list →

Use cases for BigQuery

Data Querying
"Run SQL queries on data", "Execute read-only analysis", "Use AI/ML functions"
Schema Discovery
"List datasets in project", "Browse table IDs", "Explore database structure"
Metadata Exploration
"Get table schema and metadata", "View dataset information", "Inspect column types"
AI & ML Analysis
"Forecast trends with AI", "Evaluate ML models", "Run predictive queries"

What are the risks of using the BigQuery MCP without an AI gateway?

Uncontrolled reads — AI agents can pull data out of BigQuery with no visibility into what was accessed.
Ungoverned writes — agents can create or modify records in BigQuery with no approval step.
Destructive actions — agents can delete or overwrite BigQuery data with no approval gate or audit trail.
Native OAuth is all-or-nothing — connecting directly grants an agent everything your user account can do in BigQuery, with no per-tool scoping.

Why connect BigQuery with the Barndoor AI gateway?

Barndoor MCP Governance is the gateway between your AI agents and the tools they use.
At a glance Available?
Fine-grained access controls policies per agent, team, role, user, MCP server and tool call Yes
Approval required before write/destructive actions Yes (configurable per role)
Full audit log (reads and writes) Yes
Sensitive data detection before it reaches a model or agent Yes
Instant access revocation Yes
SOC 2 Type II compliant Yes
  • Centralized MCP management — One place to manage and control every MCP server across the organization so your team has an approved catalog of MCP servers that employees and AI agents connect through.
  • Universal connection — One universal URL works across every AI provider your team uses.
  • Fine-grained access controls — Set access policies for how AI is connecting with BigQuery based on human identities, agent profiles, tool-access, context, and data fields.
  • Protect sensitive data — Keeps sensitive data from reaching a model or AI agent with PII detection, masking, tokenization, redaction, and more.
  • Observability — Real-time reporting and dashboards that give you visibility into what AI is doing with BigQuery, how policies are being enforced, and who (human or agent) is doing what.
  • Enterprise-grade security — Stay compliant with audit trails and logging.

Works with every AI client

Getting started with BigQuery in Barndoor

  1. Connect the BigQuery MCP server once
  2. Define your policies
  3. Go live across every AI client
See the full setup guide →

Frequently asked questions

What is MCP?
MCP (Model Context Protocol) is the open standard that lets AI models and agents connect to external tools and data sources through a common interface, instead of a custom integration for every tool. BigQuery is an MCP server that exposes a defined set of tools an AI agent can call. Barndoor sits at that connection point, applying access policies and audit logging to every tool call regardless of which AI client is making it.
Is Barndoor secure?
Yes. Barndoor is SOC 2 Type II compliant. Barndoor enforces fine-grained access control, requires approval before destructive actions, protects sensitive data with data loss prevention, and logs every action for audit.
How are BigQuery schema changes handled?
Barndoor tracks tool and schema changes on BigQuery. New or changed tools inherit deny-by-default access until an admin reviews and approves them, keeping runtime enforcement current without manual reconfiguration. Every schema change is captured in the audit trail alongside who approved it.
Do you integrate with my identity provider?
Barndoor authenticates admins and policy managers through your OIDC or SAML 2.0 identity provider. Signing into Claude, Cursor, or ChatGPT still happens directly with those providers. Barndoor's integration point is the BigQuery connection where access policies apply to what an agent can do once it's connected.
Do users have to enter tokens manually?
No. Barndoor brokers the OAuth connection to BigQuery centrally, so users and agents never handle or store a standing token themselves. Access is granted and revoked through policy instead of shared credentials.
How does Barndoor integrate with AI agent identities?
Barndoor gives each AI agent its own governed identity called an AgentProfile, separate from the human who configured or uses it. AgentProfile lets policies and audit logs attribute a given action to the specific agent, not a shared service token, so you can set different access rules per agent and revoke one agent's access without affecting others.
Can I deploy custom-built MCP servers?
Yes. Barndoor supports customer-built MCPs, so internal tools and systems your team builds get the same policy enforcement and audit trail as Barndoor MCPs and official MCPs.
Can I set and audit tool-level access across teams?
Yes. Barndoor's access control is fine-grained, down to the agent, team, group, user, MCP server, the specific tool call, and the data type involved. Every call is logged with a timestamp, the user or agent calling it, the client it came from, and the result of the policy applied, so you can see exactly who or what did what, when, and whether it was allowed, across any team or role.
How can I get started with BigQuery and Barndoor?
Connect BigQuery once, define your access policies, and go live across every AI client your team uses. Setup takes three steps: connect the server, define policies by role or agent, and roll out to Claude, Cursor, ChatGPT, and any other MCP-compatible client. Request a demo at barndoor.ai/get-a-demo to learn more.

Connect BigQuery to your AI agents with Barndoor.

Join AI-forward enterprises using Barndoor MCP Governance to manage and secure BigQuery integrations with AI and AI agents.