Imported from terminalskills/skills (skills/claude-mem/SKILL.md). Install upstream with npx skills add terminalskills/skills --skill claude-mem. Copyright stays with the author (Apache-2.0).

Claude Code Persistent Memory

Overview

Claude Code forgets everything between sessions. Two open-source tools solve this by automatically capturing context and injecting it into future sessions:

• claude-mem — captures session activity, compresses it with AI, injects relevant memories on next session. Lightweight, local-first.
• Claude Subconscious — a background Letta agent that watches sessions, builds up memory over time, and whispers guidance back. Cloud or self-hosted.

Both eliminate the need to re-explain context when returning to a project.

Instructions

Option A: claude-mem (Local AI Compression)

GitHub: thedotmack/claude-mem

Setup

npm install -g claude-mem
cd your-project
claude-mem init
claude-mem setup-hooks

This creates .claude-mem/ with config, compressed memories, and an index. Hooks auto-capture after each session and auto-inject before the next.

How It Works

1. Capture — hooks into Claude Code session, records interactions
2. Compress — AI summarizes session into structured memory (decisions, code changes, learnings)
3. Store — compressed memories saved to .claude-mem/ directory
4. Retrieve — on new session, relevant memories injected into context

Commands

claude-mem capture                     # Capture current session
claude-mem inject                      # Inject memories into context
claude-mem search "auth flow"          # Semantic search through memories
claude-mem list                        # List all memories
claude-mem stats                       # Show memory stats
claude-mem compress                    # Reduce storage for old memories

Configuration

{
  "compression": {
    "model": "claude-sonnet-4-20250514",
    "strategy": "smart"
  },
  "inject": {
    "maxMemories": 10,
    "relevanceThreshold": 0.7,
    "strategy": "semantic"
  }
}

Strategies: smart (AI picks what's important), full (captures everything), minimal (only decisions and errors).

Option B: Claude Subconscious (Letta Background Agent)

GitHub: letta-ai/claude-subconscious

Setup

/plugin marketplace add letta-ai/claude-subconscious
/plugin install claude-subconscious@claude-subconscious
export LETTA_API_KEY="your-api-key"

Get your API key from app.letta.com. Or self-host:

pip install letta
letta server --port 8283
export LETTA_BASE_URL="http://localhost:8283"

Modes

Which to Choose

Examples

Example 1: Session Continuity with claude-mem

# Session 1: Work on auth module
$ claude-mem stats
Memories: 12 | Storage: 45KB | Last capture: 2 hours ago

# Session 2: Return to project — auto-injected context
# Claude already knows: "You implemented JWT auth with RS256, refresh tokens in Redis"

Example 2: Architecture Recall with Subconscious

After discussing a REST-to-GraphQL migration, you start a new session:

[subconscious] Last session you decided to switch from REST to GraphQL for the
user service. Migration is 60% done — resolvers for User and Project are complete,
Order and Payment still need conversion. You preferred code-first schema with TypeGraphQL.

Guidelines

• Pair with CLAUDE.md — use CLAUDE.md for static project context, persistent memory for dynamic decisions
• One tool per project — don't run both claude-mem and Subconscious simultaneously
• For claude-mem: set relevanceThreshold higher (0.8+) if too much context is injected
• For Subconscious: whisper mode gives 90% of the value at lower token cost
• Add .claude-mem/memories/ to .gitignore for private projects
• Memory quality depends on session length — short sessions produce less useful memories