据 AlphaMoat 统计,截至 2026-09,MemoryLayer 累计下载 3,562 次、获 7 个星标,在全部 5,078 个 AI 技能中排名第 3,072 位,在「AI 智能体」分类(969 个)中排名第 622 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 86 | 2,668 | 7 | - |
| SkillHub ↗ | 450 | 3,562 | 7 | — |
各平台的计数口径不同,统计时间不一致。
文档展示记忆存储、按语义搜索、提示词上下文提取、类型和元数据标注及用量统计。访问使用账号或 API 密钥,并给出 SDK 风格示例。这些示例描述集成流程,服务可用性与所列 SDK 接口仍需验证。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,562 | — | 7 |
| 2026-08 | 3,158 | +2.3% | 7 |
| 2026-07 | 3,086 | +5.5% | 7 |
| 2026-06 | 2,925 | +4.1% | 7 |
| 2026-05 | 2,811 | — | 7 |
| 2026-03 | 2,354 | — | 7 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
---
slug: memorylayer
name: MemoryLayer
description: Semantic memory for AI agents. 95% token savings with vector search.
homepage: https://memorylayer.clawbot.hk
metadata:
clawdbot:
emoji: "🧠"
---
# MemoryLayer Semantic memory infrastructure for AI agents that actually scales. ## Features - **95% Token Savings** - Retrieve only relevant memories - **Semantic Search** - Find memories by meaning, not keywords - **Sub-200ms** - Lightning-fast memory retrieval - **Multi-tenant** - Isolated memory per agent instance ## Setup ### 1. Sign up for FREE account Visit https://memorylayer.clawbot.hk and sign up with Google. You'll get: - 10,000 operations/month - 1GB storage - Community support ### 2. Configure credentials ```bash # 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 ``` ### 3. Install Python SDK (if not using skill wrapper) ```bash pip install memorylayer ``` ## Usage ### Basic Example ```javascript // 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" ``` ### Python Example ```python 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}") ``` ### Token Savings **Before MemoryLayer:** ```python # Inject entire memory files context = open('MEMORY.md').read() # 10,500 tokens prompt = f"{context}\n\nUser: What are my preferences?" ``` **After MemoryLayer:** ```python # 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 ## API Reference ### `memory.remember(content, options)` Store a new memory. **Parameters:** - `content` (string): Memory content - `options.type` (string): 'episodic' | 'semantic' | 'procedural' - `options.importance` (number): 0.0 to 1.0 - `options.metadata` (object): Additional tags/data **Returns:** 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` ## Advanced ### Memory Types **Episodic** - Events and experiences ```javascript memory.remember('Deployed MemoryLayer on 2026-02-03', { type: 'episodic' }); ``` **Semantic** - Facts and knowledge ```javascript memory.remember('Boss prefers concise reports', { type: 'semantic' }); ``` **Procedural** - How-to and processes ```javascript memory.remember('To restart server: ssh root@... && systemctl restart...', { type: 'procedural' }); ``` ### Metadata Tagging ```javascript memory.remember('User likes blue', { type: 'semantic', metadata: { category: 'preferences', subcategory: 'colors', source: 'user_profile' } }); ``` ### Usage Tracking ```javascript 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)`); ``` ## Pricing **FREE Plan** (Current) - 10,000 operations/month - 1GB storage - Community support **Pro Plan** ($99/mo) - 1M operations/month - 10GB storage - Email support - 99.9% SLA **Enterprise** (Custom) - Unlimited operations - Unlimited storage - Dedicated support - Self-hosted option - Custom SLA ## Support - **Documentation:** https://memorylayer.clawbot.hk/docs - **API Reference:** https://memorylayer.clawbot.hk/api - **Community:** Discord (link in docs) - **Issues:** GitHub (link in docs) ## Links - **Homepage:** https://memorylayer.clawbot.hk - **Dashboard:** https://dashboard.memorylayer.clawbot.hk - **API Docs:** https://memorylayer.clawbot.hk/docs - **Python SDK:** https://pypi.org/project/memorylayer (when published)
把开发过程中的经验、错误与纠正记录为 Markdown 文件,供后续复用并晋升为工作区记忆。
用自然语言描述需求,在本地与远程技能市场里找技能并给出推荐的技能。
给 AI agent 用的浏览器自动化命令行技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在安装第三方技能之前,按清单审查来源、权限与危险模式的技能。
把 agent 的记忆与跨技能状态存成带类型和约束的知识图谱的技能。
一份为 AI 代理规划主动跟进、工作记忆与复盘流程的工作区配置指南。
指导如何创建与更新有效 Claude 技能的写作指南。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。