SleepSweet

SleepSweet is an open-source memory hygiene and audit layer for AI agents: an offline engine plus local CLI and MCP server that deduplicates, resolves conflicts, flags stale facts, finds broken links and dead paths in the memory your agent already keeps — CLAUDE.md, AGENTS.md, ~/.claude auto-memory, Cursor rules, and GitHub Copilot instructions. It is not a memory store and it does not do retrieval.

pip install sleepsweet     # or zero-install: uvx sleepsweet run
sleepsweet run             # scan + report + one confirmation + fixes with a log
sleepsweet report          # the latest report; --details for every finding
sleepsweet diff            # what changed in memory since the previous run
sleepsweet undo            # revert applied fixes; --to DATE rolls back to a date
sleepsweet asof 2026-08-01 # what the agent knew at that date

Local-first: no telemetry, no network calls, secrets redacted before anything is stored. Non-destructive: nothing changes without your y, history is marked, never deleted, and every decision is journaled — the event log can reconstruct what your agent knew at any past date.

Agents can run SleepSweet themselves via MCP (sleepsweet mcp): scan, read the stable JSON report, judge fact conflicts, dismiss false positives — no API key or model configuration needed.

Docs and source: https://github.com/sleepsweet/sleepsweet