A high-performance Redis Labs integration that enables AI agents to manage scalable data storage, vector indexes, and automated workflows seamlessly.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install redis-labs-integration
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install redis-labs-integration using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Redis Labs Integration?
The Redis Labs skill for Openclaw Skills provides a robust bridge between your AI coding agent and fully managed Redis cloud services. By leveraging this integration, developers can equip their agents with the ability to handle complex data storage, caching solutions, and vector indexing without the overhead of manual infrastructure management.
This skill is powered by the Membrane framework, which abstracts away the complexities of authentication and credential refreshing. It allows your agent to focus on executing logic and interacting with Redis keys, functions, and vector indexes through a secure, proxy-based architecture, ensuring high-performance data operations within any Openclaw Skills environment.
Redis Labs Integration Use Cases
- Managing real-time application state and caching via Redis key-value pairs.
- Implementing vector database capabilities for AI-driven semantic search and retrieval.
- Automating database maintenance tasks and workflow triggers within a cloud environment.
- Synchronizing data across distributed systems using Redis functions.
- Rapid prototyping of data-intensive features through natural language action discovery.
How Redis Labs Integration Works
- The user installs the Membrane CLI and authenticates the specific agent type to establish a secure handshake.
- A connection to Redis Labs is initiated using a normalized app URL, which Membrane uses to resolve the environment.
- The agent polls the connection state, handling any required client actions like OAuth or input provision until the state is READY.
- Natural language intent is used to search for specific Redis actions (e.g., 'get key', 'create index') within the connection context.
- The agent executes selected actions with JSON parameters or performs direct proxy requests to the Redis Labs API, with Membrane automatically injecting authentication headers.
Redis Labs Integration Setup
To get started with this skill in your Openclaw Skills workflow, follow these steps:
Install the CLI
npm install -g @membranehq/cli@latest
Authentication
Connect your agent (e.g., openclaw, claude) to the Membrane tenant:
membrane login --tenant --clientName=openclaw
Create a Connection
Establish the link to your Redis Labs instance:
membrane connection ensure "https://redislabs.com/" --json
Redis Labs Integration Data Schema & Taxonomy
The Redis Labs skill organizes data through a structured taxonomy facilitated by the Membrane registry. This ensures that Openclaw Skills can interact with predictable data shapes.
| Entity | Description |
|---|---|
| Database Key | The fundamental unit representing key-value pairs in the Redis store. |
| Vector Index | Metadata and structures used for high-dimensional vector similarity searches. |
| Redis Function | Server-side scripts and logic managed within the Redis environment. |
| Action Schema | Every discoverable action includes an inputSchema for parameters and an outputSchema for results. |
Redis Labs Integration Advanced Features
- Automatic Credential Lifecycle: Membrane handles all token refreshes and OAuth flows server-side, so no secrets are stored locally.
- Natural Language Discovery: Search for database capabilities using intent-based queries instead of hardcoded API endpoints.
- Direct API Proxy: Access the full Redis Labs API surface area via
membrane requestwhen pre-built actions do not cover specific edge cases. - Long-Polling Synchronization: Use the
--waitflag to synchronize agent workflows with asynchronous connection building processes. - Headless Mode Support: Robust CLI-based authentication for remote servers and containerized AI environments.
SKILL.md
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