Google BigQuery MCP Server
for AI Agents
Connect your AI agent to StackOne's Google BigQuery MCP server and give it 41 MCP tools out of the box. Auth, tool execution, and security all managed.
StackOne 
Coverage
41 Agent Actions
Create, read, update, and delete across Google BigQuery — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Google BigQuery MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Google BigQuery tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.
Prompt Injection Defense →
Performance
Max Agent Context. Min Cost.
Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Google BigQuery call.
Tools Discovery →What is the Google BigQuery MCP Server?
A Google BigQuery MCP server lets AI agents read and write Google BigQuery data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Google BigQuery MCP server ships with 41 pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Google BigQuery MCP Tools
Every action from Google BigQuery's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Datasets
- Create Dataset
Creates a new empty dataset
- List Datasets
Lists all datasets in the specified project
- Get Dataset
Returns the dataset specified by datasetID
- Delete Dataset
Deletes the dataset specified by datasetId
Table IAM Policys
- Get Table IAM Policy
Gets the IAM policy for the specified table
- Set Table IAM Policy
Sets the IAM policy for the specified table
Routine IAM Policys
- Get Routine IAM Policy
Gets the IAM policy for the specified routine
- Set Routine IAM Policy
Sets the IAM policy for the specified routine
Jobs
- List Jobs
Lists all jobs in the specified project
- Get Job
Returns information about a specific job
- Delete Job
Requests the deletion of the metadata of a job
Models
- List Models
Lists all models in the specified dataset
- Get Model
Gets the specified model resource
- Delete Model
Deletes the model specified by modelId
Routines
- Create Routine
Creates a new routine in the dataset
- List Routines
Lists all routines in the specified dataset
- Get Routine
Gets the specified routine resource
- Update Routine
Updates information in an existing routine
- Delete Routine
Deletes the routine specified by routineId
Tables
- Create Table
Creates a new, empty table in the dataset
- List Tables
Lists all tables in the specified dataset
- Get Table
Gets the specified table resource
- Delete Table
Deletes the table specified by tableId
Other (18)
- Create Row Access Policy
Creates a new row access policy on the specified table
- List Row Access Policies
Lists all row access policies on the specified table
- Query (Synchronous)
Runs a BigQuery SQL query synchronously and returns query results
- Get Query Results
Retrieves the results of a query job
- 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 Table Data
Lists the content of a table in rows
- Patch Dataset
Updates information in an existing dataset
- Replace Dataset
Replaces an existing dataset with a full resource update
- Undelete Dataset
Undeletes a dataset which is within time travel window
- Test Routine IAM Permissions
Tests if the caller has the specified permissions on a routine
- Test Table IAM Permissions
Tests if the caller has the specified permissions on a table
- Insert Job (Asynchronous)
Starts a new asynchronous job (query, load, extract, copy)
- Cancel Job
Requests that a job be cancelled
- Patch Model
Updates information in an existing model
- Insert Table Data
Streams data into BigQuery using the streaming insert API; supports inserting one or more rows per request
- Patch Table
Updates information in an existing table
- Replace Table
Replaces an existing table with a full resource update
Set Up Your Google BigQuery MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Google BigQuery in under 10 lines of code.
Agent Frameworks
JSON{
"mcpServers": {
"stackone": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://api.stackone.com/mcp?x-account-id=<account_id>",
"--header",
"Authorization: Basic <YOUR_BASE64_TOKEN>"
]
}
}
}Google BigQuery Resources
How I Vibe-Coded a Customer Success Hub Using StackOne's AI Native Integration Platform
How a non-developer vibe-coded a customer success dashboard pulling HubSpot, Pylon, PostHog, Databricks, and Fireflies through StackOne's MCP gateway.
7 min read
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
Indirect Prompt Injection Defense for MCP Tools: A Technical Guide
MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.
12 min
MCP vs A2A: Architecture, Security, and When to Use Each
MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.
12 min
MCP vs API: What 200+ Connector Builds Taught Us
MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.
14 min read
Google BigQuery MCP Server FAQ
Does StackOne have a Google BigQuery MCP server?
Google BigQuery MCP server vs direct API integration — what's the difference?
How does Google BigQuery authentication work for AI agents?
origin_owner_id.Are Google BigQuery MCP tools vulnerable to prompt injection?
What is the context bloat of a Google BigQuery agent and how do I avoid it?
Can I limit which actions my Google BigQuery agent can access?
Can I create custom agent actions for my Google BigQuery MCP server?
When should I NOT use a Google BigQuery MCP server?
What AI frameworks and AI clients does the StackOne Google BigQuery MCP server support?
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