Google BigQuery - Cominty Docs

Connect BigQuery so agents can list your datasets and tables, read their schemas, and run SQL queries. Cominty uses the remote BigQuery MCP server hosted by Google, at https://bigquery.googleapis.com/mcp. Google enables it when you enable the BigQuery API on your project.

Before you start

You have a Google Cloud project with the BigQuery API enabled. A new project has it enabled already.
You can create OAuth credentials in that project.
The Google account that authorizes the connection has these IAM roles on the project:
Role Why
MCP Tool User (roles/mcp.toolUser) Call MCP tools
BigQuery Job User (roles/bigquery.jobUser) Run BigQuery jobs
BigQuery Data Viewer (roles/bigquery.dataViewer) Query BigQuery data
You have the Cominty callback URL: https://mcp.cominty.com/v2/oauth/callback. See OAuth callback.

Role	Why
MCP Tool User (`roles/mcp.toolUser`)	Call MCP tools
BigQuery Job User (`roles/bigquery.jobUser`)	Run BigQuery jobs
BigQuery Data Viewer (`roles/bigquery.dataViewer`)	Query BigQuery data

Create a separate Google identity for the agents, with only the roles above, so you can control and audit what they reach. BigQuery tools can also need extra permissions on the data they read.

Create the OAuth client

Open the credentials page

In the Google Cloud console, select your project. Go to APIs & Services → Credentials, then click Create credentials → OAuth client ID.

Fill in the form

If Google asks you to configure the consent screen first, do it, then come back.

Field	Value
Application type	Web application
Name	`Cominty` or any name your team recognizes
Authorized redirect URIs	`https://mcp.cominty.com/v2/oauth/callback`

Create the client

Click Create. Copy the Client ID and the Client secret. Treat the secret like a password.

Google does not accept custom redirect URIs other than the one you register here. Paste the callback URL exactly as shown.

Connect it to Cominty

The Google BigQuery integration dialog, with the Availability choice, the Client ID and the Client secret — The Google BigQuery integration on the Integrations page of the platform

Open the integration

On platform.cominty.ai, open Integrations and choose Google BigQuery.

Choose who can use it

Under Availability, pick Organization to share the connection with everyone in your workspace (admins manage it), or Personal to keep it private to you.

Add the credentials

Under Configuration, enter the Client ID and the Client secret from Google. The OAuth scope is https://www.googleapis.com/auth/bigquery.

Tell the agent how to use it

Fill in Agent configuration. This is where you give the agent your project ID. See Tell the agent how to use BigQuery.

Connect

Click Connect, sign in with the Google account described above, and approve the access.

Test it

Ask an agent something that needs BigQuery, such as “List the datasets in the project my-project”.

A few MCP integrations need approval on the provider’s side before they connect. If the connection fails after you authorize it, or you need help, reach out to Cominty.

Tell the agent how to use BigQuery

BigQuery questions almost always need details the agent cannot guess: which project ID to query, which dataset to start from, and which tool to prefer. Put them in the integration’s Agent configuration, once, instead of typing them in every message.

The Agent configuration section of the Google BigQuery integration, with the When to use and How to use it fields — The Agent configuration section: When to use, How to use it, and Permissions

The two fields do different jobs:

Field	Read by	Use it for
When to use	The main agent, to decide when to hand a task to BigQuery	The situations and tasks BigQuery covers
How to use it	The BigQuery sub-agent that does the work	Project ID, defaults, conventions, constraints

Write the project ID in How to use it. For example:

The default project is my-analytics-project. This is the project ID, not the project name.
When the user talks about "the project", use my-analytics-project.
Start from the dataset sales unless the user names another one.
Use fully qualified table names, such as `my-analytics-project.sales.orders`.
Read the table schema with get_table_info before writing a query.
Prefer execute_sql_readonly. Use execute_sql only if the user clearly asks to change data.
Add a LIMIT when you explore a table.

To find the project ID, open the Google Cloud console and click the project selector at the top. The list shows each project’s name and its ID. They are often different. Use the ID. For the full model (what each field does, how the main agent and the sub-agent share the work, and how to write good instructions), see Connector instructions.

What agents can do

The BigQuery MCP server gives agents these tools:

Tool	What it does
`list_dataset_ids`	List the datasets of a project
`list_table_ids`	List the tables of a dataset
`get_dataset_info`	Read a dataset’s metadata
`get_table_info`	Read a table’s metadata and schema
`execute_sql`	Run a SQL query. It can change data.
`execute_sql_readonly`	Run a read-only SQL query

Example prompts:

“List the datasets in the project my-project.”
“Find the biggest orders in the dataset sales of my-project. Pick the right tables, check the schema, and show the results.”
“Create a forecast for the next months from the table my-project.sales.orders.”

Limits

Queries run for three minutes at most. Longer ones are cancelled.
A result holds 3,000 rows at most.
execute_sql_readonly allows reads only. It refuses data changes (DML), schema changes (DDL), Python user-defined functions, and Graph Query Language (GQL) queries.
Neither query tool can read Google Drive external tables.
The server has no quota of its own. The quotas of the BigQuery API behind each tool still apply.

Control what the agent can do

execute_sql is the only tool that is not read-only. To block writes, create an IAM deny policy on the project that denies the read-write tool. Google describes it in its guide to using the BigQuery MCP server. From your code, you can turn the connection off for one message, or limit a thread to some connections. See Capabilities and the use case on connections.

Troubleshooting

Symptom	Likely cause
`redirect_uri_mismatch`	The redirect URI of the OAuth client is not exactly `https://mcp.cominty.com/v2/oauth/callback`.
A permission error when the agent runs a query	The Google account is missing one of the three IAM roles, or lacks access to the dataset.
`invalid_client`	The client ID or the secret in Cominty is wrong, or the client was deleted. Copy them again from Google.
The answer stops at 3,000 rows, or a query is cancelled	These are limits of the BigQuery MCP server. Ask for aggregated results, or filter the query.
The connection stops working	The OAuth client was deleted or its secret was reset. Create a new one and update Cominty.

​Before you start

​Create the OAuth client

​Connect it to Cominty

​Tell the agent how to use BigQuery

​What agents can do

​Limits

​Control what the agent can do

​Troubleshooting

Before you start

Create the OAuth client

Connect it to Cominty

Tell the agent how to use BigQuery

What agents can do

Limits

Control what the agent can do

Troubleshooting