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Connectors Google BigQuery
Live 34 Actions

Google BigQuery integration for AI agents

Connect your AI agent to 34 production-ready Google BigQuery actions via MCP, A2A, or SDK — with managed agent tool auth, optimized execution, and built-in security.

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Google BigQuery AI agent actions

34 production-ready actions for your agent to do more on Google BigQuery.

34 Actions
List Datasets - Lists all datasets in the specified project
Get Dataset - Returns the dataset specified by datasetID
Create Dataset - Creates a new empty dataset
Update Dataset - Updates information in an existing dataset
Delete Dataset - Deletes the dataset specified by datasetId
Undelete Dataset - Undeletes a dataset which is within time travel window
Get Table IAM Policy - Gets the IAM policy for the specified table
Set Table IAM Policy - Sets the IAM policy for the specified table
Test Table IAM Permissions - Tests if the caller has the specified permissions on a table
Run Query (Synchronous) - Runs a BigQuery SQL query synchronously and returns query results
Insert Job (Asynchronous) - Starts a new asynchronous job (query, load, extract, copy)
List Jobs - Lists all jobs in the specified project
Get Job - Returns information about a specific job
Get Query Results - Retrieves the results of a query job
Cancel Job - Requests that a job be cancelled
Delete Job - Requests the deletion of the metadata of a job
List Models - Lists all models in the specified dataset
Get Model - Gets the specified model resource
Update Model - Updates information in an existing model
Delete Model - Deletes the model specified by modelId
List Projects - Lists all projects to which the user has been granted any project role
Get Service Account - Returns the email address of the service account for the project
List Routines - Lists all routines in the specified dataset
Get Routine - Gets the specified routine resource
Create Routine - Creates a new routine in the dataset
Update Routine - Updates information in an existing routine
Delete Routine - Deletes the routine specified by routineId
List Table Data - Lists the content of a table in rows
Insert Table Data - Streams data into BigQuery using the streaming insert API; supports inserting one or more rows per request
List Tables - Lists all tables in the specified dataset
Get Table - Gets the specified table resource
Create Table - Creates a new, empty table in the dataset
Update Table - Updates information in an existing table
Delete Table - Deletes the table specified by tableId

Do More, Build Less.

Integration Infrastructure for Google BigQuery AI Agents.

Multiple Interfaces

Access integrations via API, AI SDKs, MCP & A2A.

Google BigQuery MCP server
Managed Authentication

Pre-built authentication UI.

Agent auth
Falcon Engine

Every Google BigQuery action runs on Falcon.

Agent Execution Engine
StackOne Defender
StackOne Defender Meta PG v1 Meta PG v2 DeBERTa 88.7% 67.5% 63.1% 56.9% Detection accuracy

88.7% prompt injection detection.

Prompt injection defense

"What impressed us most about StackOne is its ambition and clarity. They're creating infrastructure that modern software and the entire AI agent ecosystem can rely on. The depth of secure integrations, the pace of delivery, and the team's foresight into AI's future uniquely position StackOne to redefine this category."

Luna Schmid, Partner at GV

"We've been impressed by how quickly and deeply StackOne integrates with complex enterprise systems -- and now, with their focus on agent-to-agent interoperability, they're unlocking even more powerful use cases for customers. StackOne delivers all of the above in a universal layer -- without compromise."

Barbry McGann, SVP at Workday Ventures

G2 - High Performer G2 - Easiest To Do Business With G2 - Users Love Us G2 - Users Most Likely To Recommend G2 - Easiest Admin

Product teams love building agent integrations with StackOne.

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Google BigQuery agent integration resources

Agentic Context Engineering: Why AI Agents Kill Their Own Context Windows

AI agents exceed their context windows without knowing it. Six failure patterns and seven survival architectures for agentic context engineering.

15 min

MCP Code Mode: Keeping Tool Responses Out of Agent Context

Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.

11 min

Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery

Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.

10 min

Put your AI agents to work

All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.