The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the LocalKeep listing page.
LocalKeep is for anyone who wants a chronological memory layer for chatbots where they directly control what the model remembers about them. Instead of forcing you to rely on a black-box cloud memory that the model invents around you that you can't even edit, LocalKeep lets you curate titled, dated, editable memory banks directly on your own machine where you write the entries and manage them locally via a localhost Hub UI. When a conversation requires your prior context, Claude queries your local data through a secure, native Model Context Protocol (MCP) connector.
AI Chat apps are great at sounding like they remember you, but struggle at recalling the exact thing you care about — what happened, on which date, about whom? Consumer memory features tend to lack the capacity for true temporal reasoning, flattening your history into a soft, generic vibe summary instead of understanding that Event A triggered Event B three months ago, causing its reasoning to fail when you need something specific: a life event, a research arc, a decision you logged months ago. Worse yet, consumer AI memory is a black box: you don't get to decide what the model chooses to remember about you, how it interprets your life, or when it invents context around you.
LocalKeep fixes both structural flaws at once by replacing fragile, model-invented timelines with a rigid, chronological source of your truth, all while giving you absolute editorial control. You decide exactly what the AI is allowed to know about you. You write the entries, you anchor the dates, and you keep them local on your own machine. Claude simply acts as the lookup engine via MCP when a conversation requires your prior context. LocalKeep bridges the gap between structured personal logging and intelligent AI retrieval, ensuring your context is curated by you—not hallucinated by an LLM.
Who it’s for
What it is (and isn’t)
The Hub UI intentionally adopts a retro, Windows 95/MS Paint-inspired homage with customizable features to ensure LocalKeep feels like a deeply personal tool rather than an impersonal, rigid dashboard. By putting adjustable interface elements right at your fingertips, the UI signals that you are entering an intimate, offline workshop for your mind—a space you can shape and reconfigure to feel entirely like your own.
Then:
In Claude Desktop, register the MCP server (claude_desktop_config.json):
If the GUI can’t find localkeep-mcp on your PATH, use the absolute path from which localkeep-mcp (the Hub’s Connect panel copies this for you).
Memories default to ~/.localkeep/localkeep.db when installed via pip. Override with LOCALKEEP_DATA_DIR or LOCALKEEP_DB_PATH.
Claude will not reliably call MCP tools unless you also set Personal preferences:
src/localkeep/assets/claude-personal-preferences.txt)From a source checkout, the DB lives in data/localkeep.db (gitignored).
These smoke-check the Hub, retrieval, and MCP tools so a fresh install still stores and recalls dated memories the way a real user would.
Tests start from an empty DB and create memories through Hub form POSTs (same path as a new user).
Storage is local. Banks and memories live in your chosen DB path (~/.localkeep/ for pip installs, or data/localkeep.db in a checkout). There is no LocalKeep cloud and nothing is auto-scraped from chat. Theme colors stay in browser localStorage. Refreshing the Hub page or restarting localkeep-hub does not delete your banks — only removing the database file does.
Recall goes through Claude. The Hub and database stay on your machine, but when Claude calls a LocalKeep MCP tool, the matching memories are returned into that chat and Anthropic processes them like any other tool result. LocalKeep isn’t shipping your whole DB upstream — only what that lookup returns for the question at hand.
Bug reports and pull requests are welcome via GitHub Issues. Please run uv run pytest before opening a PR.
MIT — see LICENSE.