Agent Memory Hub
БесплатноНе проверенEnables AI agents to store, search, and retrieve long-term memories with BM25 full-text search, auto-tagging, and importance scoring.
Описание
Enables AI agents to store, search, and retrieve long-term memories with BM25 full-text search, auto-tagging, and importance scoring.
README
Persistent, intelligent, searchable long-term memory for AI agents.
Store facts, preferences, notes, and project context. Retrieve them with full-text BM25 search, importance scoring, and recency weighting. No API keys. No external servers. Works out of the box.
Features
- 7 powerful tools — store, search, retrieve context, update, list, forget, summarize
- BM25 full-text search — proper ranked search with IDF, not just string matching
- Auto-tagging — automatically infers categories (preference, project, technical, task, credential, etc.)
- Auto importance scoring — detects urgency signals in content
- Recency + importance weighting — more relevant memories surface first
- Atomic writes — corruption-safe file persistence
- Zero dependencies — only the MCP SDK; no native binaries, no Python, no Docker
- Configurable storage — override path with
AGENT_MEMORY_DIRenv var
Installation
1. Clone and build
git clone https://github.com/yourname/agent-memory-hub
cd agent-memory-hub
npm install
npm run build
2. Add to Claude Desktop
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"agent-memory-hub": {
"command": "node",
"args": ["C:\\Users\\HP\\agent-memory-hub\\build\\index.js"]
}
}
}
3. Add to Claude Code (MCP CLI)
claude mcp add agent-memory-hub -- node "C:\Users\HP\agent-memory-hub\build\index.js"
Custom storage directory
{
"mcpServers": {
"agent-memory-hub": {
"command": "node",
"args": ["C:\\Users\\HP\\agent-memory-hub\\build\\index.js"],
"env": {
"AGENT_MEMORY_DIR": "C:\\Users\\HP\\my-agent-memories"
}
}
}
}
Default storage: ~/.agent-memory/memories.json
Tools
store_memory
Store any piece of information worth remembering.
key: "user_preferred_language"
content: "User always prefers TypeScript over JavaScript"
tags: ["preference", "technical"] ← auto-detected if omitted
importance: 7 ← auto-scored if omitted
overwrite: true ← upsert: update if key exists, create if not
By default, storing a key that already exists returns an error. Set overwrite: true to silently update the existing memory instead — useful when you want "set this value" semantics without checking first.
search_memory
BM25 full-text search across all memories.
query: "typescript preferences"
limit: 5 ← optional, default 5
tags: ["technical"] ← optional filter
get_relevant_context
Auto-retrieve the best memories for a given query. Use this at session start.
user_query: "Help me set up the project authentication"
→ Returns: identity memories, project memories, technical preferences
update_memory
Modify existing memory content, tags, or importance.
key: "user_preferred_language"
new_content: "User prefers TypeScript, but accepts Python for scripts"
importance: 8
list_memories
Browse memories with sorting and filtering.
tags: ["project"]
sort: "importance" ← "recent" | "importance" | "access"
limit: 10
forget_memory
Permanently delete a memory.
key: "old_api_key"
memory_summary
Get a full overview — counts, top tags, most important and most accessed memories.
Storage Format
Memories are stored as plain JSON at ~/.agent-memory/memories.json. Human-readable, easy to backup or inspect.
{
"version": "1.0.0",
"created": "2025-01-01T00:00:00.000Z",
"lastUpdated": "2025-06-01T12:00:00.000Z",
"memories": [
{
"id": "uuid",
"key": "user_preferred_language",
"content": "User prefers TypeScript over JavaScript",
"tags": ["preference", "technical"],
"importance": 7,
"createdAt": "...",
"updatedAt": "...",
"accessCount": 12,
"lastAccessed": "..."
}
]
}
Auto-Tagging Categories
The system auto-detects these categories from content:
| Tag | Trigger signals |
|---|---|
preference |
prefer, like, love, hate, favorite, avoid |
project |
project, working on, building, repository |
identity |
I am, my name, I work, my role |
technical |
code, api, database, framework, docker |
task |
todo, must, deadline, remind |
credential |
password, secret, token, api key |
note |
note, remember that, fyi, heads up |
person |
name is, email, phone, contact |
config |
config, setting, env var, port, url |
Development
npm run dev # watch mode
npm run build # production build
License
MIT
Установить Agent Memory Hub в Claude Desktop, Claude Code, Cursor
unyly install agent-memory-hubСтавит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.
Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh
Или настроить вручную
Выполни в терминале:
claude mcp add agent-memory-hub -- npx -y github:AIsofialuz/agent-memory-hubFAQ
Agent Memory Hub MCP бесплатный?
Да, Agent Memory Hub MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Agent Memory Hub?
Нет, Agent Memory Hub работает без API-ключей и переменных окружения.
Agent Memory Hub — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Agent Memory Hub в Claude Desktop, Claude Code или Cursor?
Открой Agent Memory Hub на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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