A powerful skill that enables AI agents to manage graph-relational data, execute EdgeQL queries, and automate schema migrations through Membrane.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install edgedb
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 edgedb 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 EdgeDB Integration for AI Agents?
The EdgeDB skill for Openclaw Skills provides a seamless bridge between AI coding agents and EdgeDB, a graph-relational database designed for high-performance data modeling. By leveraging the Membrane framework, this skill removes the complexity of manual authentication and credential management, allowing agents to focus on data logic and application structure.
Using this integration, developers can empower their AI agents to handle complex data relationships that traditional SQL or ORMs find cumbersome. It provides a robust set of tools for schema evolution and data manipulation, ensuring high data integrity and developer productivity across the entire development lifecycle.
EdgeDB Integration for AI Agents Use Cases
- Automating database schema migrations during the development process.
- Executing complex EdgeQL queries to retrieve or manipulate relational data.
- Managing application records and automating data-driven workflows.
- Integrating graph-based data structures into AI-driven backend services.
- Inspecting database client versions and connection health programmatically.
How EdgeDB Integration for AI Agents Works
- The AI agent authenticates with the Membrane platform using a specific tenant and client type.
- A connection is established to the EdgeDB instance, with Membrane handling all OAuth or API key handshakes.
- The agent polls the connection status to ensure it is in a READY state before proceeding.
- Available actions are discovered using natural language intent searches (e.g., searching for 'QUERY' actions).
- The agent executes specific actions like SchemaCreateMigration or ExecuteEdgeQL by passing JSON-formatted parameters.
- For edge cases not covered by pre-built actions, the agent uses the Membrane proxy to send direct, authenticated requests to the EdgeDB API.
EdgeDB Integration for AI Agents Setup
To get started with this integration in Openclaw Skills, install the Membrane CLI:
npm install -g @membranehq/cli@latest
Authenticate your agent environment:
membrane login --tenant --clientName=openclaw
Establish a connection to your EdgeDB instance:
membrane connection ensure "https://www.edgedb.com/" --json
EdgeDB Integration for AI Agents Data Schema & Taxonomy
The skill organizes its operations into specialized modules to maintain data integrity and clear taxonomy:
| Category | Actions | Purpose |
|---|---|---|
| Schema | SchemaCreateMigration, SchemaApplyNextMigration | Handles version control and structural changes of the database. |
| Query | ExecuteEdgeQL | Manages data retrieval and manipulation using EdgeQL syntax. |
| Client | GetClientVersion | Provides metadata regarding the EdgeDB environment. |
| Proxy | membrane request | Allows raw API interaction with automatic header injection. |
EdgeDB Integration for AI Agents Advanced Features
- Automatic credential refreshing ensuring long-running AI workflows are never interrupted by expired tokens.
- Long-polling connection management using the --wait flag to handle asynchronous environment setups.
- Natural language action discovery to map developer intent to specific database operations.
- Headless authentication support for remote servers and CI/CD environments.
- JSON-wrapped output for all commands to facilitate machine readability and agent parsing.
SKILL.md
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