# cursor-mem0

> cursor-mem0 — xwqiang-cursor-mem0. Use this tool when you need to integrate AI agent memory with the Cursor SDK, enabling local embeddings and efficient data retrieval via Qdrant and MCP. It solves problems related to AI model memory management, providing a seamless interface for CURSOR_API_KEY authentication and git compatibility. Ideal for use cases requiring secure and efficient AI data storage and retrieval in the Cursor IDE.

Canonical page: https://skillsregistry.net/skills/xwqiang-cursor-mem0  
JSON: https://api.skillsregistry.net/v1/skills/xwqiang-cursor-mem0

## Description

mem0-compatible AI agent memory via Cursor SDK (CURSOR_API_KEY). Local embeddings, Qdrant, MCP for Cursor IDE.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/xwqiang/cursor-mem0)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "xwqiang-cursor-mem0"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/xwqiang-cursor-mem0` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/xwqiang-cursor-mem0/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt