forgememo 0.2.10

Persistent memory for AI agents — cross-session context that actually sticks

Forgememo

Persistent long-term memory for AI agents — cross-session context that actually sticks.

Forgememo mines your git history, session traces, and project notes to extract what actually happened — failures, successes, plans, and hard-won lessons. It stores them locally in SQLite and exposes them to AI agents via MCP so they start every session informed instead of blind.

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The Problem

Every new agent session starts from zero. It doesn't know you already tried the Zod 4 schema approach and it broke. It doesn't know that wildcard CORS killed auth in production last quarter. It doesn't know which approach you abandoned and why.

Without Forgememo, agents repeat your mistakes. With it, they skip straight to what works.

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Installation

pip install forgememo
forgememo init

forgememo init now requires a real TTY on first run so the user must choose an inference provider interactively. Agents cannot bypass that step with --yes or a piped session. After init completes, start the daemon with forgememo start; then restart your AI agent (Claude Code, Gemini CLI, or Codex) to pick up the MCP connection.

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How It Works

1. Hook — tool events are normalized and sent to the daemon (socket-first).
2. Daemon — single write path, dedup, event queue.
3. Worker — distills raw events into durable summaries.
4. Store — SQLite holds events, distilled_summaries, and session_summaries.
5. Serve — MCP tools query the daemon API (read-only).

Agents call search_memories and get_memory_details to pull prior context without re-learning it.

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Quick Start

# Install
pip install forgememo

# Initialize (interactive on first run)
forgememo init

# Start the daemon + worker (macOS LaunchAgents)
forgememo start

# Optional: enable legacy mining on a schedule
forgememo start --mine

# Restart your agent, then verify
forgememo status

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Agent Support

Agent	Hook config
Claude Code	integrations/claude-code/settings-snippet.json
OpenAI Codex	integrations/codex/config-snippet.yaml
OpenCode	integrations/opencode/config-snippet.json
Gemini CLI	integrations/gemini/settings-snippet.json

Run the interactive setup script to wire up your tool:

bash integrations/setup.sh

For Claude Code it auto-applies the hooks block to ~/.claude/settings.json. For other tools it prints the snippet to merge manually.

forgememo init also detects Claude Code, Gemini CLI, and Codex and writes the appropriate skill file automatically. Agents call search_memories and get_memory_details via MCP — no extra configuration beyond the hook.

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MCP Tools

Tool	Description
search_memories	Compact index search (IDs + titles)
get_memory_details	Full content for specific IDs
get_memory_timeline	Temporal context around a distilled summary
save_session_summary	Write a structured session summary via daemon
get_session_summary	Retrieve recent session summaries
retrieve_memories	Deprecated alias for search_memories

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CLI Reference

forgememo init                # Initialize DB, choose provider, register MCP, write skill files
forgememo start               # Start daemon + worker (macOS LaunchAgents)
forgememo start --mine        # Also install a scheduled mining agent (hourly, legacy)
forgememo stop                # Stop daemon + worker
forgememo status              # Show DB stats, server health, skill status
forgememo export-context      # Write CLAUDE.md / AGENTS.md context blocks
forgememo daemon              # Run daemon in foreground
forgememo worker              # Run worker in foreground
forgememo store "<text>"      # Save a memory trace manually
forgememo search "<query>"    # Search stored memories
forgememo mine                # Scan repos and session files for new learnings
forgememo distill             # Condense undistilled traces into principles
forgememo config              # Set inference provider (anthropic / ollama / gemini / …)
forgememo auth login          # Authenticate for managed inference (no BYOK needed)

Legacy trace/principle commands (store, search, mine, distill) remain for backward compatibility.

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Inference Providers

Forgememo uses an LLM for mining and distillation. Three options:

Provider	Setup	Cost
Forgememo managed	choose it in forgememo init, then run forgememo auth login	Free tier + paid plans
Ollama (local)	choose it in forgememo init	Free, fully private
BYOK (Anthropic / OpenAI / Gemini)	forgememo config <provider> --key <key>	Your API costs

forgememo init now requires the user to choose a provider interactively on first run.

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Platform Support

Platform	Daemon + Worker	Auto-start
macOS	LaunchAgents (launchctl)	On login
Linux	systemd user services (instructions printed)	Manual
Windows	Task Scheduler (command printed)	Manual

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Licensing

Forgememo is Apache-2.0 for community use.

• Community — Apache-2.0, permissive, local-first, commercial-friendly
• Enterprise — hosted terms with SLA, SSO/SAML, audit logs, priority support, and private hosting
• Contributing — all contributors must sign the CLA by adding their name to CONTRIBUTORS.md in their first PR