Agent Memory Hub
FreeNot checkedEnables AI agents to store, search, and retrieve long-term memories with BM25 full-text search, auto-tagging, and importance scoring.
About
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
Install Agent Memory Hub in Claude Desktop, Claude Code & Cursor
unyly install agent-memory-hubInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add agent-memory-hub -- npx -y github:AIsofialuz/agent-memory-hubFAQ
Is Agent Memory Hub MCP free?
Yes, Agent Memory Hub MCP is free — one-click install via Unyly at no cost.
Does Agent Memory Hub need an API key?
No, Agent Memory Hub runs without API keys or environment variables.
Is Agent Memory Hub hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Agent Memory Hub in Claude Desktop, Claude Code or Cursor?
Open Agent Memory Hub on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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