vertex-ai-search
Interact with the Vertex AI Search API via natural language commands
Open source Open in the app JSON README (API)
About
Interact with the Vertex AI Search API via natural language commands
Details
- Kind
- Plugins
- Topic
- No topic detected
- Publisher
- gemini-cli-extensions
- Origin
- gemini
- Category
- ferramentas
- Version
- 1.0.0
- Stars
- 1
- Last push
- 2026-04-20T21:54:39Z
- 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/vertex-ai-search
README
# Vertex AI Search Managed MCP Extension
The Vertex AI Search managed MCP extension allows users to interact with the
Vertex AI Search API via natural language commands.
## Why use the Vertex AI Search 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
[Vertex AI Search API](https://console.cloud.google.com/marketplace/product/google/discoveryengine.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/vertex-ai-search
```
## Available tools
To see a complete list of available tools and their schemas, see the
[Vertex AI Search MCP reference](https://docs.cloud.google.com/generative-ai-app-builder/docs/reference/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 Vertex AI Search MCP server doesn't have its own quotas. There is no limit
on the number of call 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
[Vertex AI Search remote MCP server reference documentation](https://docs.cloud.google.com/generative-ai-app-builder/docs/reference/mcp),
which includes a list of all available tools, and the full input and output
schema for each tool.
* See the
[Vertex AI Search overview](https://docs.cloud.google.com/generative-ai-app-builder/docs).
* Learn about
[MCP security and governance](https://docs.cloud.google.com/mcp/ai-security-safety).