Semantic memory for AI agents. 95% token savings with vector search.
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install memorylayer或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install memorylayer⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/memorylayer/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- slug: memorylayer name: MemoryLayer description: Semantic memory for AI agents. 95% token savings with vector search. homepage: https://memorylayer.clawbot.hk metadata: clawdbot: emoji: "🧠" ---
Semantic memory infrastructure for AI agents that actually scales.
Visit https://memorylayer.clawbot.hk and sign up with Google. You'll get:
# Option 1: Email/Password
export [email protected]
export MEMORYLAYER_PASSWORD=your_password
# Option 2: API Key (recommended for production)
export MEMORYLAYER_API_KEY=ml_your_api_key_here
pip install memorylayer
// In your Clawdbot agent
const memory = require('memorylayer');
// Store a memory
await memory.remember(
'User prefers dark mode UI',
{ type: 'semantic', importance: 0.8 }
);
// Search memories
const results = await memory.search('UI preferences');
console.log(results[0].content); // "User prefers dark mode UI"
from plugins.memorylayer import memory
# Store
memory.remember(
"Boss prefers direct reporting with zero bullshit",
memory_type="semantic",
importance=0.9
)
# Search
results = memory.recall("What are Boss's preferences?")
for r in results:
print(f"{r.relevance_score:.2f}: {r.memory.content}")
Before MemoryLayer:
# Inject entire memory files
context = open('MEMORY.md').read() # 10,500 tokens
prompt = f"{context}\n\nUser: What are my preferences?"
After MemoryLayer:
# Inject only relevant memories
context = memory.get_context("user preferences", limit=5) # ~500 tokens
prompt = f"{context}\n\nUser: What are my preferences?"
Result: 95% token reduction, $900/month savings at scale
memory.remember(content, options)Store a new memory.
Parameters:
content (string): Memory contentoptions.type (string): 'episodic' | 'semantic' | 'procedural'options.importance (number): 0.0 to 1.0options.metadata (object): Additional tags/dataReturns: Memory object with id
memory.search(query, limit)Search memories semantically.
Parameters:
query (string): Search query (natural language)limit (number): Max results (default: 10)Returns: Array of SearchResult objects
memory.get_context(query, limit)Get formatted context for prompt injection.
Parameters:
query (string): What context do you need?limit (number): Max memories (default: 5)Returns: Formatted string ready for prompt
memory.stats()Get usage statistics.
Returns: Object with total_memories, memory_types, operations_this_month
Episodic - Events and experiences
memory.remember('Deployed MemoryLayer on 2026-02-03', { type: 'episodic' });
Semantic - Facts and knowledge
memory.remember('Boss prefers concise reports', { type: 'semantic' });
Procedural - How-to and processes
memory.remember('To restart server: ssh root@... && systemctl restart...', { type: 'procedural' });
memory.remember('User likes blue', {
type: 'semantic',
metadata: {
category: 'preferences',
subcategory: 'colors',
source: 'user_profile'
}
});
const stats = await memory.stats();
console.log(`Total memories: ${stats.total_memories}`);
console.log(`Operations this month: ${stats.operations_this_month}`);
console.log(`Plan: ${stats.plan} (${stats.operations_limit}/month)`);
FREE Plan (Current)
Pro Plan ($99/mo)
Enterprise (Custom)
安装 MemoryLayer 后,可以对 AI 说这些话来触发它
Help me get started with MemoryLayer
Explains what MemoryLayer does, walks through the setup, and runs a quick demo based on your current project
Use MemoryLayer to semantic memory for AI agents
Invokes MemoryLayer with the right parameters and returns the result directly in the conversation
What can I do with MemoryLayer in my documents & notes workflow?
Lists the top use cases for MemoryLayer, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/memorylayer/ 目录(个人级,所有项目可用),或 .claude/skills/memorylayer/(项目级)。重启 AI 客户端后,用 /memorylayer 主动调用,或让 AI 根据上下文自动发现并使用。
MemoryLayer 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
MemoryLayer 可免费安装使用。请查阅仓库了解许可证信息。
Semantic memory for AI agents. 95% token savings with vector search.
MemoryLayer 属于「Documents & Notes」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my documents & notes tasks using MemoryLayer
Identifies repetitive steps in your workflow and sets up MemoryLayer to handle them automatically