A specialized skill to integrate Alibaba Cloud Tablestore as a persistent long-term memory backend for AI agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install alibabacloud-tablestore-openclaw-memory
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 alibabacloud-tablestore-openclaw-memory 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 Alibaba Cloud Tablestore Mem0 for OpenClaw?
The Alibaba Cloud Tablestore Mem0 skill provides a robust architecture for maintaining persistent memory in AI systems. By leveraging Alibaba Cloud Tablestore as a high-performance vector store, this skill allows Openclaw Skills to store, retrieve, and manage long-term contextual data seamlessly. It is designed for developers who require enterprise-grade reliability and scalability for their agentic workflows, ensuring that important user facts and conversation history are never lost.
This integration specifically utilizes the Tablestore vector store backend for the Mem0 framework. It simplifies the process of creating a durable memory layer, enabling Openclaw Skills to act on previous interactions and evolving user needs without manual context re-injection.
Alibaba Cloud Tablestore Mem0 for OpenClaw Use Cases
- Storing and recalling user-specific preferences across different sessions.
- Managing complex context for multi-agent workflows within Openclaw Skills.
- Auto-provisioning cloud-based vector databases for rapid prototyping.
- Implementing secure, role-based memory access using Alibaba Cloud ECS RAM Roles.
How Alibaba Cloud Tablestore Mem0 for OpenClaw Works
- Validates Alibaba Cloud credentials or ECS RAM Role permissions to ensure secure access.
- Installs the specific version of the @tablestore/openclaw-mem0 plugin into the local environment.
- Detects the existing configuration and automatically creates a Tablestore instance if one is not provided.
- Configures the memory slot in the local gateway settings to utilize the Tablestore provider.
- Connects with DashScope embeddings via an OpenAI-compatible interface to process vector data.
- Restarts the service to finalize the memory persistent layer for all Openclaw Skills.
Alibaba Cloud Tablestore Mem0 for OpenClaw Setup
To begin, collect your Alibaba Cloud credentials and DashScope API Key. Install the required plugin version using the following command:
openclaw plugins install @tablestore/[email protected]
Configure your environment variables to ensure secure credential management for your Openclaw Skills:
export TABLESTORE_ACCESS_KEY_ID="<your-id>"
export TABLESTORE_ACCESS_KEY_SECRET="<your-secret>"
export DASHSCOPE_API_KEY="<your-api-key>"
Finally, update your configuration file and restart the gateway to enable the new memory backend:
openclaw gateway restart
Alibaba Cloud Tablestore Mem0 for OpenClaw Data Schema & Taxonomy
The skill utilizes a structured approach to manage vector data within Tablestore. Below is the technical data organization used by Openclaw Skills:
| Parameter | Description | Default Value |
|---|---|---|
| tableName | The primary data table for vectors | mem0_vectors |
| dimension | Embedding vector size for Qwen | 1024 |
| vectorStore | The underlying backend provider | tablestore |
| embedder | Provider for text embeddings | openai (DashScope) |
| regionId | Deployment region for auto-provisioning | cn-hangzhou |
Alibaba Cloud Tablestore Mem0 for OpenClaw Advanced Features
- Zero-configuration auto-provisioning of VCU-based Tablestore instances for pay-as-you-go efficiency.
- Cross-region support allowing for data sovereignty and latency optimization across Alibaba Cloud zones.
- Native support for Alibaba Cloud RAM Roles to eliminate hardcoded credentials in Openclaw Skills.
- Automatic fallback logic to enable public internet endpoints if VPC connectivity is restricted.
- Integrated support for the text-embedding-v3 model and Qwen-Plus for high-accuracy memory retrieval.
SKILL.md
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