claude-memory

A persistent, semantic memory system for Claude Code, exposed as an MCP server. Instead of re-reading flat markdown files each session, Claude searches a vector database by meaning — surfacing prior decisions, evolved thinking, and relevant context automatically.

It also includes a judgment ledger: log predictions and assessments, resolve them later against reality, and generate calibration patterns and bias maps so the assistant learns where your judgment is systematically off.

How it works

• Storage — ChromaDB vector store on disk (./chroma_db).

• Embeddings — OpenAI (text-embedding-3 family) for semantic similarity.

• Synthesis — Anthropic Claude for context briefs, consolidation, calibration, and bias maps.

• Retrieval — memories are ranked by relevance × salience, so important context surfaces first.

Memories are typed: episodic (events/decisions), semantic (extracted patterns, usually written by consolidation), user (facts about you), feedback (how to work with you), project (ongoing initiatives), reference (pointers to external systems).

Related MCP server: MemoVault

Tools

Memory

• search_memory — semantic search over all memories

• save_memory — persist a decision, insight, or piece of context

• get_context_brief — Claude-synthesized brief on a topic (what's known, how thinking evolved, what to challenge)

• get_related — memories related to a given one

• consolidate — extract durable semantic patterns from recent episodes

• list_memories, memory_stats — inspect the store

Judgment ledger

• log_assessment — record a prediction with confidence, horizon, and reasoning

• list_pending_assessments — assessments awaiting resolution

• resolve_assessment — score what actually happened (right / partial / wrong)

• generate_calibration — extract a calibration pattern for a domain (needs 3+ resolved)

• get_bias_map — cross-domain map of where judgment is strong vs. poor

Setup

Requires Python 3.12+.

git clone https://github.com/allenc84/claude-memory.git
cd claude-memory
python3.12 -m venv venv
./venv/bin/pip install -r requirements.txt
cp .env.example .env   # then edit .env

Set your keys and persona in .env (see .env.example):

MEMORY_USER_CONTEXT="Jane Doe, founder of Acme"
OPENAI_API_KEY=sk-proj-...
ANTHROPIC_API_KEY=sk-ant-...

On macOS, run_server.sh reads the API keys from the Keychain if present, falling back to .env:

security add-generic-password -U -s "OPENAI_API_KEY"    -a "claude-memory" -w 'sk-proj-...'
security add-generic-password -U -s "ANTHROPIC_API_KEY" -a "claude-memory" -w 'sk-ant-...'

Pass the key as the -w argument, not via the interactive prompt — the prompt truncates at 128 characters and silently corrupts longer keys.

Wire into Claude Code

Add to your MCP config (e.g. ~/.claude.json or project .mcp.json):

{
  "mcpServers": {
    "claude-memory": {
      "command": "/absolute/path/to/claude-memory/run_server.sh"
    }
  }
}

Restart Claude Code. The server caches keys and config at launch, so restart after changing either.

The /log command

.claude/commands/log.md provides a /log slash command for the judgment ledger — logging, reviewing, resolving, and generating calibrations/bias maps in natural language. Copy it into your project's .claude/commands/ to use it.

Automation (optional)

• run_consolidate.sh — nightly: extract semantic patterns from recent episodes. Schedule via cron/launchd.

• run_weekly_review.sh — weekly judgment-ledger review; designed to be triggered from a Claude Code Stop hook.

Migrating existing markdown memories

To import legacy flat-file memories into the vector store:

MEMORY_MIGRATE_DIR="$HOME/path/to/memory" ./venv/bin/python migrate.py

License

MIT — see LICENSE.