linggen-memory
A semantic memory store for AI assistants.
ling-mem is a single-binary CLI + optional web UI that remembers useful facts about you and your work across every session, every tool, and every project. LanceDB-backed, local-first, markdown-native where it counts.
Built as the default memory skill for Linggen; works equally well invoked from Claude Code or any tool that can shell out.
🚀 Status: v0.7.0 — prebuilt binaries available for macOS Apple Silicon and Linux (x86_64 + aarch64). Active development on main. The pre-refactor code-indexing tool is preserved at the v0-legacy git tag.
What it does
- Remembers across sessions. Facts about who you are, how you prefer to work, what you've tried, what worked, what didn't.
- Semantic retrieval. Everything stored gets embedded (1024-dim via
Qwen3-Embedding-0.6B, multilingual). Find "berth calibration" by asking about "dock alignment."
- Typed facts. Four default categories —
fact / preference / decision / learned — plus tried / fixed / built for trajectory-level patterns.
- Forgetting is first-class.
delete by id, forget by filter — refuses empty filters as a guardrail.
- Self-updating.
ling-mem upgrade --check reports the latest release; ling-mem start, restart, and status all embed the same cached probe in their JSON so the agent can prompt the user when a new version ships without making extra network calls. upgrade --yes swaps the binary atomically and restarts the daemon. (self-update still works as an alias.)
- Three ways to use it:
- As the
shared-memory skill on Linggen — web app UI + Memory_* tool dispatch in the agent.
- As the
shared-memory skill on Claude Code / Codex / OpenClaw — SKILL.md body, model calls the CLI via Bash, recall hook injects context every turn.
- Standalone — any script or tool can shell out to
ling-mem.
See doc/product-spec.md for the full product story and doc/tech-spec.md for the implementation contract.
Quick look
# Add a fact
ling-mem add "prefers concise replies, no hedging" \
--type preference --from user
# Semantic search
ling-mem search "how do I format logs in dev" \
--context code/linggen --limit 5
# Browse by filter
ling-mem list --type preference --since 2026-01-01 --format text
# Forget a finished project
ling-mem forget --context trip-japan-2026 --yes
Default output is NDJSON on stdout — any model / script / shell can parse it. Pass --format text for human-readable lines.
The daemon (ling-mem start) also serves a built-in Data Browser at http://127.0.0.1:9888 for hands-on filter / edit / batch-delete.
Install
The ling-mem binary ships as part of the shared-memory skill (in the linggen/skills repo at shared-memory/). Installing the skill is the recommended path — it fetches the prebuilt binary, wires up the SKILL.md, and seeds the core memory files.
Best experience: Linggen agent, which exposes typed Memory_query / Memory_write tools and a built-in dashboard. The skill also works with any other agent that can shell out (Claude Code, Codex, OpenClaw, plain scripts) — they just call the ling-mem CLI directly.
# One-liner installer (cross-host: drops the canonical bundle at
# ~/.linggen/skills/shared-memory and per-host stubs under
# ~/.claude/, ~/.codex/, ~/.openclaw/ if those dirs exist):
curl -fsSL https://linggen.dev/install-shared-memory.sh | bash
# Or from a checked-out clone:
git clone https://github.com/linggen/skills
cd skills/shared-memory
./install.sh # auto-detects every host runtime
LING_MEM_VERSION=v0.7.0 ./install.sh # pin a specific binary version
Prebuilt binaries are available for macOS Apple Silicon and Linux (x86_64 + aarch64) on the releases page.
To build from source instead:
git clone https://github.com/linggen/linggen-memory
cd linggen-memory
cargo build --release
./target/release/ling-mem --help
See doc/tech-spec.md → Release process for the cross-compile + signing flow.
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