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Redis Cloud API MCP Server

Redis Cloud API MCP Server

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github.com/redisDatabases43Updated 77w ago

About Redis Cloud API MCP Server

Redis Cloud API MCP Server is an MCP server for the Redis Cloud API that lets users manage accounts, subscriptions, plans and tasks in natural language. It suits users who want to work with Redis Cloud from Claude Desktop or another MCP client.

Key features

  1. 01Query account details and payment methods
  2. 02List, create and delete Pro and Essential subscriptions
  3. 03Query database modules and cloud regions
  4. 04List Essential plans with pagination
  5. 05List and inspect asynchronous tasks

Use cases

  1. 01Create a Redis database subscription through natural language
  2. 02Review current subscriptions and payment methods
  3. 03Track the status of long-running operations

MCP support

This project is an MCP server that exposes Redis Cloud API operations for accounts, subscriptions, plans, regions and tasks as tools to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"redis-cloud": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/inspector"
]
}
}
}
Run commandnpx -y @modelcontextprotocol/inspector

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@modelcontextprotocol/inspector

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Redis Cloud API MCP Server

Model Context Protocol (MCP) is a standardized protocol for managing context between large language models (LLMs) and external systems. This repository provides an MCP Server for Redis Cloud's API, allowing you to manage your Redis Cloud resources using natural language.

This lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things on your Redis Cloud account, e.g.:

  • "Create a new Redis database in AWS"
  • "What are my current subscriptions?"
  • "Help me choose the right Redis database for my e-commerce application"

Features

Account Management
  • get_current_account: Get details about your current Redis Cloud account
  • get_current_payment_methods: List all payment methods configured for your account
Subscription Management
Pro Subscriptions
  • get_pro_subscriptions: List all Pro subscriptions in your account
  • create_pro_subscription: Create a new Pro subscription with advanced configuration options
    • Supports multi-cloud deployment
    • Configure memory, persistence, and modules
    • Set up Active-Active deployments
    • Custom networking configuration
Essential Subscriptions
  • get_essential_subscriptions: List all Essential subscriptions (paginated)
  • get_essential_subscription_by_id: Get detailed information about a specific Essential subscription
  • create_essential_subscription: Create a new Essential subscription
  • delete_essential_subscription: Delete an Essential subscription
Database Capabilities
  • get_database_modules: List all available database modules (capabilities) supported in your account
    • Redis modules
    • Database features
    • Performance options
Cloud Provider Management
  • get_pro_plans_regions: Get available regions across cloud providers
    • AWS regions
    • GCP regions
    • Networking options
    • Availability zones
Plans and Pricing
  • get_essentials_plans: List available Essential subscription plans (paginated)
    • Supports AWS, GCP, and Azure
    • Redis Flex options
    • Fixed plans
Task Management
  • get_tasks: List all current tasks in your account
  • get_task_by_id: Get detailed information about a specific task
    • Track deployment status
    • Monitor subscription changes
    • View task progress

Usage

Prerequisites
  • Valid Redis Cloud API credentials (API Key and Secret Key)
  • Task IDs are returned for long-running operations and can be monitored
  • Paginated responses require multiple calls to retrieve all data
Claude Desktop

To run the MCP server with Claude Desktop, follow these steps:

  1. Build the package:

    npm run build
    
  2. Add the server to Claude Desktop:

    • Open Claude Desktop settings
    • Navigate to the Developer tab (make sure you have enabled Developer Mode)
    • Click on "Edit config"
    • Open the claude_desktop_config.json file in your text editor and add the following configuration:
    {
      "mcpServers": {
        "mcp-redis-cloud": {
          "command": "node",
          "args": ["--experimental-fetch", "<absolute_path_to_project_root>/dist/index.js"],
          "env": {
            "API_KEY": "<redis_cloud_api_key>",
            "SECRET_KEY": "<redis_cloud_api_secret_key>"
          }
        }
      }
    }
    
  3. Close Claude Desktop and restart it. The server should now be available in the MCP Servers section.

Cursor IDE

To run the MCP server with Cursor IDE, follow these steps:

  1. Build the package:

    npm run build
    
  2. Add the server to Cursor:

    • Open Cursor Settings
    • Navigate to the MCP tab
    • Click on "Add new global MCP Server"
    • Update the automatically opened mcp.json file with the following configuration:
    {
      "mcpServers": {
        "mcp-redis-cloud": {
          "command": "node",
          "args": ["--experimental-fetch", "<absolute_path_to_project_root>/dist/index.js"],
          "env": {
            "API_KEY": "<redis_cloud_api_key>",
            "SECRET_KEY": "<redis_cloud_api_secret_key>"
          }
        }
      }
    }
    
  3. Restart Cursor. The server should now be available in the MCP Servers section.

Development

Prerequisites
  1. nvm (Node Version Manager)
  2. Node v22.14.0
  3. npm 10.9.2
Getting Started
  1. Install dependencies:

    nvm use v22.14.0
    npm install
    
  2. Build the project:

    npm run build
    
  3. Test it by using the MCP Inspector:

    npx @modelcontextprotocol/inspector node dist/index.js --api-key=<api_key> --secret-key=<secret_key>
    
Project Structure
src/
├── index.ts              # Entry point
├── clients/              # API Clients for external services
│   └── generated         # Generated Redis Cloud API client
└── tools/                # Tool implementations
    └── accounts/         # Account tools
    └── subscriptions/    # Subscription tools
    └── tasks/            # Task tools

Note: If you make changes to your code, remember to rebuild and restart Claude Desktop / Cursor:

npm run build

Docker Usage

Building the Docker Image

To build the Docker image for the MCP server, run the following command:

docker build -t mcp/redis-cloud .
Running the Docker Container

To run the container, use the following command:

docker run -i --rm \
  -e API_KEY=<your_redis_cloud_api_key> \
  -e SECRET_KEY=<your_redis_cloud_api_secret_key> \
  mcp/redis-cloud
Docker Integration with Claude Desktop

To integrate the Dockerized MCP server with Claude Desktop, follow these steps:

  1. Build the Docker image (if you haven't already):

    docker build -t mcp/redis-cloud .
    
  2. Add the server to Claude Desktop:

    • Open Claude Desktop settings
    • Navigate to the Developer tab (ensure Developer Mode is enabled)
    • Click on "Edit config"
    • Open the claude_desktop_config.json file in your text editor
    • Add the following configuration:
    {
      "mcpServers": {
        "redis-cloud": {
          "command": "docker",
          "args": [
            "run",
            "-i",
            "--rm",
            "-e",
            "API_KEY=<your_redis_cloud_api_key>",
            "-e",
            "SECRET_KEY=<your_redis_cloud_api_secret_key>",
            "mcp/redis-cloud"
          ]
        }
      }
    }
    
  3. Replace the placeholder values with your actual API credentials.

  4. Save the configuration file and restart Claude Desktop.

Notes
  • Ensure that the required environment variables (API_KEY, SECRET_KEY) are set correctly.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.