agent-memory-hub

agent-memory-hub

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_DIR env 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

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:

Development

npm run dev    # watch mode
npm run build  # production build

License

MIT