memorystore-for-redis
Manage Memorystore for Redis instances using natural language.
Open source Open in the app JSON README (API)
About
Manage Memorystore for Redis instances using natural language.
Details
- Kind
- Plugins
- Topic
- Databases
- Publisher
- gemini-cli-extensions
- Origin
- gemini
- Category
- ferramentas
- Version
- 1.0.0
- Last push
- 2026-04-20T20:06:05Z
- 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/memorystore-for-redis
README
# Memorystore for Redis Managed MCP Extension
The Memorystore for Redis managed MCP extension lets you manage Memorystore for
Redis instances from your AI-enabled development environments and AI agent
platforms.
## Why use the Memorystore for Redis 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
[Memorystore for Redis API](https://console.cloud.google.com/marketplace/product/google/redis.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/memorystore-for-redis
```
## Available tools
To see a complete list of available tools and their schemas, see the
[Memorystore for Redis MCP reference](https://docs.cloud.google.com/memorystore/docs/redis/reference/mcp).
## Sample use cases
The following are sample use cases for the Memorystore for Redis MCP server:
- "Why do you create a Memorystore for Redis instance with authentication
enabled?"
By creating an instance and enabling the AUTH feature for it, incoming
client connections must authenticate to connect to the instance. To connect,
the client sends the AUTH command and an AUTH string, which is a randomly
generated string that's unique for the instance. The AI agent of the
Memorystore for Redis MCP server uses the create_instance MCP tool to create
the instance.
- "Why do you view all active Memorystore for Redis instances in a specific
region?"
By listing these instances, you can ensure that resources match your current
architecture. The AI agent of the Memorystore for Redis MCP server uses the
list_instances MCP tool to retrieve a formatted list of instances in the
specified region.
- "Why do you retrieve connection endpoints and operational metadata from a
Memorystore for Redis instance in a specific region?"
You need this information for application integration and system
maintenance. The AI agent of the Memorystore for Redis MCP server uses the
get_instance MCP tool to retrieve information about the instance, such as
its discovery endpoint and replica count.
- "How can you optimize Memorystore for Redis for your data-intensive
applications?"
To increase both the CPU capacity and the memory throughput for these
applications significantly, you can scale a Memorystore for Redis instance
by increasing the instance's replica count. The AI agent of the Memorystore
for Redis MCP server uses the update_instance MCP tool to update the replica
count for the instance.
- "How can you protect your data from failures that might occur from either a
Memorystore for Redis instance or the region where it's located?"
Export a snapshot of the data in your instance to a Cloud Storage bucket. If
a regional or instance failure occurs, then you can restore your data to a
new instance to resume operations. The AI agent of the Memorystore for Redis
MCP server uses the export_instance MCP tool to export your data.
## 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 Memorystore for Redis 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
[Memorystore for Redis remote MCP server reference documentation](https://docs.cloud.google.com/memorystore/docs/redis/reference/mcp),
which includes a list of all available tools, and the full input and output
schema for each tool.
* See the
[Memorystore for Redis overview](https://docs.cloud.google.com/memorystore/docs/redis).
* Learn about
[MCP security and governance](https://docs.cloud.google.com/mcp/ai-security-safety).