memd¶
memd is a local memory CLI for coding agents and AI scientists. Each trusted
machine gets one shared, persistent store: raw searchable content, structured
task history, and canonical collaboration artifacts. A hybrid dense + sparse
stack indexes it; an explicit trust boundary decides what counts as verified.
Agents retrieve bounded context with memd agent-context or memd search,
read the generated context file, and record durable progress with memd add.
For low-latency local use, memd keeps the store and indexes hot through a
private CLI-managed warm worker driven by ordinary CLI commands.
What memd does¶
| Surface | Purpose | Primary CLI commands |
|---|---|---|
| Raw memory | Store and search chunks: code, docs, notes, traces, decisions | memd add, memd search, memd get, memd stats |
| Agent context | Bounded pre-work context + JSON audit logs | memd agent-context --output .memd/context.md |
| Startup memory | Refresh project memory.md with latest project state, ranked fact libraries, and concrete action guidance |
memd memory-md, memd eval-memory-md --agent-usefulness |
| Usefulness report | Usage-ledger and store self-diagnosis for growth, learning, retrieval, and warnings | memd report --strict |
| Warm CLI | Keep store/index state hot for repeated local calls | memd warm start, memd warm status |
| Batch CLI | Many structured operations in one loaded process | memd batch --jsonl requests.jsonl |
| Export/import | Manual cross-machine moves through portable OMF | memd export-omf, memd import-omf |
| Operations | Structured memory / task / artifact / context / code / debug ops | memd call task.start --json '{...}' |
| Guardrails | Pin tenant/project scope and verify CLI-first agent wiring | memd init, memd doctor |
What hybrid retrieval buys¶
LoCoMo retrieval over 1,531 questions, one build, one corpus, one machine. Only the retrieval path varies, so the comparison isolates fusion from everything else:
| Retrieval | MRR@10 | p50 latency |
|---|---|---|
| hybrid (dense + BM25, RRF) | 0.4766 | 27.0 ms |
| dense only | 0.3230 | 21.3 ms |
| BM25 only | 0.3376 | 8.3 ms |
Fusion adds 0.139 MRR@10 over the better single channel at roughly 3x the sparse-only latency.
Cross-system accuracy numbers are not published here. Comparing memory systems requires every system to share a pinned dataset, answer model, judge, retrieval depth, and token budget, with per-item rows bound to an immutable manifest; that evidence lives in the benchmark repository. See Benchmarking for the contract.
Start here¶
- Quick start — install, store first memory, retrieve, build agent context.
- Operational contract — what agents should write, avoid, verify, and clean up.
- Architecture — hybrid retrieval, storage, trust boundary diagram.
- CLI reference — every command and operation.
- Agent skill — install
memdinto Claude Code / Codex with one command.