Claude Mnemonic

Give Claude Code a memory that actually remembers.

---

Claude Code forgets everything when your session ends. Claude Mnemonic fixes that.

It captures what Claude learns during your coding sessions - bug fixes, architecture decisions, patterns that work - and brings that knowledge back in future conversations. No more re-explaining your codebase.

Requirements

Dependency	Required	Purpose
Claude Code CLI	Yes	Host application (this is a plugin)
jq	Yes	JSON processing during installation

That's it. No Python. No external services. Everything runs locally.

No API keys needed! Claude Mnemonic uses Claude Code CLI, which works with your existing Claude Pro or Max subscription. No separate API costs.

Install

One command. That's it.

curl -sSL https://raw.githubusercontent.com/lukaszraczylo/claude-mnemonic/main/scripts/install.sh | bash

Windows (PowerShell)

irm https://raw.githubusercontent.com/lukaszraczylo/claude-mnemonic/main/scripts/install.ps1 | iex

Build from source

git clone https://github.com/lukaszraczylo/claude-mnemonic.git
cd claude-mnemonic
make build && make install

Requires: Go 1.24+, Node.js 18+, CGO-compatible compiler

After install, open http://localhost:37777 to see the dashboard. Start a new Claude Code session - memory is now active.

Verifying Release Signatures

All release checksums are signed with cosign using keyless signing. To verify:

# Download the checksum file and its sigstore bundle from the release
cosign verify-blob \
  --certificate-identity-regexp "https://github.com/lukaszraczylo/claude-mnemonic/.*" \
  --certificate-oidc-issuer "https://token.actions.githubusercontent.com" \
  --bundle "checksums.txt.sigstore.json" \
  checksums.txt

What it does

Feature	Description
Persistent Memory	Observations survive across sessions and restarts
Project Isolation	Each project has its own knowledge base
Global Patterns	Best practices are shared across all projects
Semantic Search	Find relevant context with natural language
Live Statusline	Real-time metrics in Claude Code: `[mnemonic] ● served:42
Web Dashboard	Browse and manage memories at localhost:37777

How knowledge flows

You code with Claude
        ↓
Claude learns something useful
        ↓
Mnemonic captures it automatically
        ↓
Next session: Claude remembers

Behind the scenes: hooks capture Claude's observations → SQLite stores with full-text search → sqlite-vec enables semantic search with local embeddings (all-MiniLM-L6-v2) → relevant context is injected at session start.

Configuration

Config file: ~/.claude-mnemonic/settings.json

{
  "CLAUDE_MNEMONIC_WORKER_PORT": 37777,
  "CLAUDE_MNEMONIC_CONTEXT_OBSERVATIONS": 100,
  "CLAUDE_MNEMONIC_CONTEXT_FULL_COUNT": 25
}

Variable	Default	What it does
WORKER_PORT	37777	Dashboard & API port
CONTEXT_OBSERVATIONS	100	Max memories per session
CONTEXT_FULL_COUNT	25	Full detail memories (rest are condensed to title only)
CONTEXT_SESSION_COUNT	10	Recent sessions to reference

Project vs Global scope

Observations are automatically scoped:

• Project scope (default) - stays within the project directory
• Global scope - shared everywhere

Global scope triggers on tags like: best-practice, security, architecture, pattern, performance

Example: A bug fix in your auth module stays local. "Always validate JWT server-side" goes global.

MCP Tools

These search tools are available via MCP:

• search - semantic search across all memories
• timeline - browse by time
• decisions - find architecture decisions
• changes - find code modifications
• how_it_works - system understanding queries

Troubleshooting

Worker won't start?

lsof -i :37777              # check if port is in use
cat /tmp/claude-mnemonic-worker.log  # view logs

Database locked?

rm -f ~/.claude-mnemonic/*.db-wal ~/.claude-mnemonic/*.db-shm

Uninstall

# Remove everything
curl -sSL https://raw.githubusercontent.com/lukaszraczylo/claude-mnemonic/main/scripts/uninstall.sh | bash

# Keep your data
curl -sSL https://raw.githubusercontent.com/lukaszraczylo/claude-mnemonic/main/scripts/uninstall.sh | bash -s -- --keep-data

Architecture

• SQLite + FTS5 - Full-text search for exact matches
• sqlite-vec - Vector database embedded in SQLite
• all-MiniLM-L6-v2 - Local embedding model (384 dimensions) via ONNX Runtime
• Go - Single binary, no external dependencies

Everything runs locally. No Python. No external vector database. No API calls for embeddings.

Platform support

Platform	Status
macOS Intel	Supported
macOS Apple Silicon	Supported
Linux amd64	Supported
Linux arm64	Supported
Windows amd64	Supported

Development

make build          # build all
make test           # run tests
make dev            # dev mode with hot reload
make install        # install to Claude plugins

License

MIT

---

Links: Releases · Issues