OpenClaw

Memos Search

MemOS External Memory Service

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查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install hope7709/memos-search

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

MemOS - External Memory Service

MemOS provides persistent memory storage via REST API.

API Base URL

{{MEMOS_API_URL}}

Available Endpoints

Add Memory

POST /add
Body: {"content": "...", "source": "agent/filename.md"}

Read Memory

GET /read/{agent}/{filename}

List Memories

GET /memories

Search Memories

POST /search
Body: {"query": "...", "top_k": 3}

Delete Memory

DELETE /delete/{agent}/{filename}

List Agents

GET /agents

Health Check

GET /health

Usage Examples

Add memory:

import requests
requests.post('{{MEMOS_API_URL}}/add', json={
    'content': '咖啡大佬今天教我使用MemOS',
    'source': 'alin/2026-02-23.md'
})

Read memory:

import requests
r = requests.get('{{MEMOS_API_URL}}/read/alin/2026-02-23.md')
print(r.json()['content'])

Search memory:

import requests
r = requests.post('{{MEMOS_API_URL}}/search', json={
    'query': '咖啡大佬教了什么',
    'top_k': 3
})
for item in r.json():
    print(f"{item['source']}: {item['score']}")

Delete memory:

import requests
requests.delete('{{MEMOS_API_URL}}/delete/alin/2026-02-23.md')

List all agents:

import requests
r = requests.get('{{MEMOS_API_URL}}/agents')
for agent in r.json()['agents']:
    print(f"{agent['name']}: {agent['file_count']} files")

Notes

Use Python requests library for API calls
Always use json= parameter (not raw body) for POST requests
File path format: {agent}/{filename}.md
API returns JSON with content field for read operations
Delete removes both file and vector index
Run MemOS server: python D:\AI\MemOS\api_server.py

来源信息

Source: github
Repository: openclaw/skills
Path: skills/hope7709/memos-search
Version: —
Commit: d0fc4f4ead7a8059e11a1d27cca452031f98b212
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# MemOS - External Memory Service

MemOS provides persistent memory storage via REST API.

## API Base URL
```
{{MEMOS_API_URL}}
```

## Available Endpoints

### Add Memory
```bash
POST /add
Body: {"content": "...", "source": "agent/filename.md"}
```

### Read Memory
```bash
GET /read/{agent}/{filename}
```

### List Memories
```bash
GET /memories
```

### Search Memories
```bash
POST /search
Body: {"query": "...", "top_k": 3}
```

### Delete Memory
```bash
DELETE /delete/{agent}/{filename}
```

### List Agents
```bash
GET /agents
```

### Health Check
```bash
GET /health
```

## Usage Examples

**Add memory:**
```python
import requests
requests.post('{{MEMOS_API_URL}}/add', json={
    'content': '咖啡大佬今天教我使用MemOS',
    'source': 'alin/2026-02-23.md'
})
```

**Read memory:**
```python
import requests
r = requests.get('{{MEMOS_API_URL}}/read/alin/2026-02-23.md')
print(r.json()['content'])
```

**Search memory:**
```python
import requests
r = requests.post('{{MEMOS_API_URL}}/search', json={
    'query': '咖啡大佬教了什么',
    'top_k': 3
})
for item in r.json():
    print(f"{item['source']}: {item['score']}")
```

**Delete memory:**
```python
import requests
requests.delete('{{MEMOS_API_URL}}/delete/alin/2026-02-23.md')
```

**List all agents:**
```python
import requests
r = requests.get('{{MEMOS_API_URL}}/agents')
for agent in r.json()['agents']:
    print(f"{agent['name']}: {agent['file_count']} files")
```

## Notes

- Use Python `requests` library for API calls
- Always use `json=` parameter (not raw body) for POST requests
- File path format: `{agent}/{filename}.md`
- API returns JSON with `content` field for read operations
- Delete removes both file and vector index
- Run MemOS server: `python D:\AI\MemOS\api_server.py`

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