Persistent memory for AI agents — store, retrieve and search knowledge across sessions
Project description
Agent Memory MCP Server 🧠
Persistent memory for AI agents — store, retrieve and search knowledge across sessions. No more forgetting between conversations.
The Problem
AI agents lose all context when a session ends. This MCP server gives agents a persistent knowledge store that survives across sessions, tools, and even different agent frameworks.
Features
- Store & Retrieve — Key-value storage with full persistence
- Namespaces — Separate memories by project, user, or context
- Tags — Categorize memories for easy filtering
- Full-Text Search — Search across all stored knowledge
- Access Tracking — See which memories are accessed most
- Statistics — Dashboard showing memory usage
Installation
pip install agent-memory-mcp-server
Usage with Claude Code
{
"mcpServers": {
"memory": {
"command": "uvx",
"args": ["agent-memory-mcp-server"]
}
}
}
Tools
| Tool | Description |
|---|---|
memory_store |
Store a key-value pair persistently |
memory_retrieve |
Retrieve stored knowledge by key |
memory_search |
Full-text search across all memories |
memory_list |
List all memories in a namespace |
memory_delete |
Remove a memory |
memory_namespaces |
List all namespaces |
memory_stats |
Usage statistics |
Examples
"Remember that the user prefers dark mode"
"What do you know about Project Alpha?"
"Store this API response for later"
"What were the key decisions from last session?"
How It Works
Uses SQLite for zero-configuration persistent storage. Data is stored locally — no cloud, no API keys, no costs. The database file (memory.db) is created automatically in the server directory.
License
MIT
Project details
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