bigquery-data-transfer-service
Manage BQTS resources such as data sources, transfer configs and transfer runs via natural language commands.
Open source Open in the app JSON README (API)
About
Manage BQTS resources such as data sources, transfer configs and transfer runs via natural language commands.
Details
- Kind
- Plugins
- Topic
- Databases
- Publisher
- gemini-cli-extensions
- Origin
- gemini
- Category
- ferramentas
- Version
- 1.0.0
- Last push
- 2026-04-20T21:07:14Z
- Repository state
- ativo
- License
- Apache-2.0
- Added
- 2026-08-30 14:13:39
- Updated
- 2026-08-30 14:13:39
- Origin id
gemini-cli-extensions/bigquery-data-transfer-service
README
# BigQuery Data Transfer Service Managed MCP Extension
> **Preview:** This product is subject to the "Pre-GA Offerings Terms" in the
> General Service Terms section of the
> [Service Specific Terms](https://docs.cloud.google.com/terms/service-terms#1).
> Pre-GA products and features are available "as is" and might have limited
> support. For more information, see the
> [launch stage descriptions](https://cloud.google.com/products#product-launch-stages).
The BigQuery Data Transfer Service managed MCP extension allows users to manage
BQTS resources such as data sources, transfer configs and transfer runs via
natural language commands.
## Why use the BigQuery Data Transfer Service managed MCP server?
Google and Google Cloud
[managed MCP servers](https://docs.cloud.google.com/mcp/overview) can be used in
your AI applications with enterprise-ready governance, security, and access
control.
## Before you begin
1. In the Google Cloud console, on the
[project selector page](https://console.cloud.google.com/projectselector2/home/dashboard),
select or create a Google Cloud project. > **Note**: If you don't plan to
keep the resources that you create in this > procedure, create a project
instead of selecting an existing project. > After you finish these steps,
you can delete the project, removing all > resources associated with the
project.
2. Get your administrator to grant you the
[MCP Tool User role](https://docs.cloud.google.com/iam/docs/roles-permissions/mcp#mcp.toolUser)
(`roles/mcp.toolUser`) on the Google Cloud project. If you created a new
project, then you already have the required permissions.
3. Ensure your administrator has enabled the
[BigQuery Data Transfer API](https://console.cloud.google.com/marketplace/product/google/bigquerydatatransfer.googleapis.com)
on the Google Cloud project.
## Configure authentication
This extension uses Google Application Default Credentials (ADC) to perform
authentication. To login with ADC, run the following command in your terminal:
```bash
gcloud auth application-default login
```
For additional details, see the
[ADC documentation](https://docs.cloud.google.com/docs/authentication/application-default-credentials#personal).
## Install the extension
To install the extension, run the following command in your terminal:
```bash
gemini extensions install https://github.com/gemini-cli-extensions/bigquery-data-transfer-service
```
## Available tools
To see a complete list of available tools and their schemas, see the
[BigQuery Data Transfer Service MCP reference](https://docs.cloud.google.com/bigquery/docs/reference/datatransfer/mcp).
## Optional security and safety configurations
MCP introduces new security risks and considerations due to the wide variety of
actions that you can take with MCP tools. To minimize and manage these risks,
Google Cloud offers defaults and customizable policies to control the use of MCP
tools in your Google Cloud organization or project. For more information about
MCP security and governance, see
[AI security and safety](https://docs.cloud.google.com/mcp/ai-security-safety).
## Quotas and limits
The BigQuery Data Transfer Service MCP server doesn't have its own quotas. There
is no limit on the number of calls that can be made to the MCP server. You are
still subject to the quotas enforced by the APIs called by the MCP server tools.
## Reference and resources
* Explore the
[BigQuery Data Transfer Service remote MCP server reference documentation](https://docs.cloud.google.com/bigquery/docs/reference/datatransfer/mcp),
which includes a list of all available tools, and the full input and output
schema for each tool.
* See the
[BigQuery Data Transfer Service overview](https://docs.cloud.google.com/bigquery/docs/dts-introduction).
* Learn about
[MCP security and governance](https://docs.cloud.google.com/mcp/ai-security-safety).