Show HN: NexusMem – local memory for coding agents, not just Git log NexusMem, a local memory tool for coding agents, records shell commands, git history, and project docs into a SQLite database, serving ranked, token-budgeted slices on demand. The tool, requiring Node 22 or newer and git, uses BM25 and vector search fused with Reciprocal Rank Fusion, and keeps all data on disk with no cloud or telemetry. In a two-day test on its own repository, NexusMem indexed 527 nodes, including 321 shell commands and 16 git commits, capturing information that git log alone cannot provide. Your coding agent can read git log . It cannot read the four things you tried last Tuesday that didn't work. NexusMem records what actually happened on your machine shell commands and their exit codes, git history down to the patch of each changed file, project docs, optionally your assistant transcripts into a local SQLite database, and serves back a ranked, token-budgeted slice of it on demand. Everything stays on disk. No account, no cloud, no telemetry. The shell history is the part worth caring about. Git tells an agent what shipped. Shell history tells it what was attempted, in what order, and which commands exited non-zero. That information exists nowhere else, and it disappears when your terminal scrollback rolls over. From inside any git repository: npx nexusmem init npx nexusmem sync Then ask it something. Real output from this repository, top 2 of 5 hits: bash $ nexusmem query "windows spawn failure" Relevant history for: windows spawn failure - 2026-08-09 fix: distinguish a failed git spawn from "not a git repository" readRepoInfo collapsed three unrelated failures into one error: git running and reporting the path is not a work tree, git not being installed, and the process failing to spawn at all. Dogfooding hit the third case in two separate sessions... - 2026-08-09 README.md — Before a tagged release - Retry on transient process-spawn failures on Windows A commit and a docs section, ranked against each other, inside whatever token budget you gave it. Nothing was summarized by a model on the way out; the ranker just decided what not to send. One optional source, session summaries, does run a local model — but at ingest time, never on the way out. What you query is always stored text. For a sense of what actually accumulates, here is nexusmem status on this repo after two days: 527 node s 2026-08-08 .. 2026-08-09 321 shell command 130 conversation turn 60 doc section 16 git commit Sixteen commits. Three hundred and twenty-one shell commands. The commits were already retrievable by any agent with a terminal. The rest was not. That conversation turn row only appears because this corpus was synced with --conversation . Assistant transcripts are the one source that is off by default and stays off until you opt in, since they are the likeliest place for a pasted credential to be sitting. A default install indexes git commits, their diffs, shell and docs. Requirements: Node 22 or newer, and git. Node 20 will not work, because better-sqlite3 ships no prebuilt binary for it and Node 20 went end-of-life in April 2026. Ollama is optional and only affects semantic search see below . Every source normalizes to the same MemoryNode shape, so a commit, a shell command and a docs section compete on equal terms. Retrieval runs BM25 over FTS5 and, if an embedding model is reachable, a vector search over sqlite-vec , then fuses the two with Reciprocal Rank Fusion. RRF fuses on rank position only, never on raw scores. That is the entire reason it is safe here: a BM25 cost and a vector distance live on unrelated, unbounded scales, and position is the only thing they agree on. No hand-tuned normalization constant sits between them. Ranking then multiplies three factors: score = relevance × signal^0.215 × recency^0.288 relevance comes from the query. signal a fix: commit outranks a chore: ; a command that exited non-zero outranks one that succeeded and recency are priors that hold before any query exists. Each factor is floored into floor, 1 rather than 0, 1 , so one weak dimension cannot zero out a strong match. Those exponents are derived, not tuned. Priors kept overturning the query: on one real query a fix: commit took rank 1 from a better-matching docs section on a 44% signal edge against a 15% relevance deficit. So the priors get a shared budget — across their whole range they may overturn at most a 2× relevance gap — split evenly between them, and each is raised to the power that makes its own span worth exactly its share span^exponent = √2 . Priors still order equally-relevant hits exactly as before, since the transform is monotonic. They just cannot outvote the question anymore. The budget is shared rather than per-prior for a reason found by dogfooding, not by reading the arithmetic: the score multiplies the priors, so capping each at 2× separately left the pair free to overturn 4×. That describes every commit made during an active working day — fresh and high-signal at once — so the failure landed on precisely the days with the most worth remembering. A query about the PowerShell hook returned two unrelated same-day fix: commits at ranks 3 and 4 while the section that answered it sat at rank 6. Adding a third prior now re-divides the same budget instead of enlarging it. Without Ollama, vector search is skipped and you get BM25 only. That path is fully supported, not a degraded error state; sync and query both succeed and simply do less. With sources.session.enabled , each finished session becomes one distilled node next to the raw exchanges — what was decided and why, rather than forty individual turns. It runs a local Ollama chat model qwen2.5:3b by default ; nothing is downloaded automatically and nothing leaves the machine. nexusmem scan-session --dry-run That prints the exact prompt a session would produce, after redaction and budget trimming, without calling the model. Three things bound the cost. A session is only summarized once it has been quiet for settleMinutes default 30 , so a session in progress is not re-summarized on every sync. The prompt is hashed, and an unchanged hash skips the model entirely — on this repo a steady-state sync of 14 summarized sessions takes 0.25s and makes no model calls. And maxSessions default 10 caps how many reach the model per run; the rest are reported as queued and picked up next sync. What it is actually like, measured on 14 real sessions with qwen2.5:3b. The summaries themselves are good: decisions with their reasons, in the shape the prompt asks for. Titles are less reliable — the model returned a usable one about a third of the time, and otherwise produced a conversational preamble, a stray bullet, or a bare "Summary of the Session". Those are rejected and the title falls back to the first line of the question that opened the session, which is always specific even when it is not elegant. Compliance was worst on long sessions and on transcripts not in English. A larger model qwen2.5:7b is the lever if the titles matter to you; set sources.session.model . { "mcpServers": { "nexusmem": { "command": "npx", "args": "-y", "nexusmem", "mcp" } } } Three tools over stdio: search memory returns the packed context block, sync project ingests, and get status reports what is currently remembered. Each takes an explicit projectRoot , because an MCP tool call carries no shell working directory. sync project runs init for you if the repository has not been set up. Scraped history files PSReadLine, .bash history , .zsh history give you command text and not much else. The hook gives you working directory, exit code and a real timestamp: nexusmem hook install It wraps your existing PowerShell prompt rather than replacing it, is idempotent, and nexusmem hook remove undoes it cleanly. Exit codes are what make this worth installing. A failed command is a stronger signal than a successful one, and without the hook there is no way to tell them apart. Two numbers get conflated in tools like this, so they are kept apart here. Packer efficiency is how much the ranker trims from its own candidate set. On this repository's corpus it runs 81–84%. It is useful for tuning the ranker and useless as a claim about your bill, because the baseline is hypothetical: without NexusMem those candidates were never going into your context window in the first place. End-to-end saving compares packed context against reading the equivalent files in full. Measured at ~40% on design queries against this codebase, hand-tallied from one real session rather than instrumented. Treat it as an order of magnitude. The long-term target is 70%, and this repository cannot demonstrate it. That figure describes repos with thousands of commits, where the win comes from omitting hundreds of unrelated items rather than shaving a handful. A benchmark at that size is still outstanding, and until it exists the honest number is 40%. One thing that is not a percentage: shell commands and conversation turns have no cheap grep equivalent. Without something recording them, they are gone, not merely more expensive to find. Latency on a ~530-node corpus, warm, p50 over 10 runs: | Operation | | |---|---| | BM25 retrieval FTS5 | ~1.1 ms | Vector KNN sqlite-vec | ~3.2 ms | | Fuse, rank, pack | ~0.6 ms | | Query embedding local Ollama | ~55–77 ms | End-to-end hybrid | ~56 ms | All the SQLite work totals about 5 ms. The embedding call is the only thing on this path worth optimizing, and it is somebody else's process. Shell history without the hook is unscoped. Scraped history has no directory context, so it is attributed to whichever repository you ran sync from. Bounded to a tail window, and an approximation rather than a guarantee. Japanese and Chinese depend on the vector pass. FTS5's unicode61 tokenizer splits on whitespace, so languages without space boundaries get no useful BM25 recall. Rebasing strands nodes. Rewritten history leaves nodes for unreachable commits. They describe real events so they are not wrong, but a targeted prune does not exist yet. sync --rebuild forces a clean re-scan. Multi-line PowerShell input is read as separate commands. A function typed across several lines at the prompt is not reconstructed. Scrape-fallback ids drift if the history file is trimmed from the front between syncs. Installing the hook fixes this. Session-summary titles depend on the model following instructions , and a 3B model often does not. The fallback keeps them specific rather than generic, but see the section above for what to expect. Changing the embedding model re-embeds everything. Vectors from two models are not comparable and nodes vec records no per-row provenance, so sync drops the lot and rebuilds rather than ranking across a mixture. It says so when it happens. Nodes are untouched and BM25 keeps working throughout. Diff indexing is bounded, and deliberately lossy. A first sync indexes the patches of the most recent 200 commits later syncs only walk cursor..HEAD ; merge commits contribute none, since their patch exists only in a combined format this parser does not read; and binaries, lockfiles and build output are skipped so a dependency bump cannot bury the corpus. All of it is still recorded as a git commit node. A patch longer than limits.maxBodyChars is truncated, so the tail of a very large change is not indexed. The caps live under sources.diff in config.json . Cross-project recall favours breadth. Each repository's hits are fused by rank, so a project whose best match is mediocre still contributes a rank-1 item, and rank 1 is worth the same in every list. Adding a repository that has little to say about your question still pushes a few of its results into the budget. Signal, recency and the budget are what hold that in check; there is no per-project quality weight. The project registry is an index, not a source of truth. It can point at a database that has moved or been deleted; those are reported and skipped, never silently pruned, because an unmounted drive is not a deleted project. Conversation chunking is unevaluated. Splitting long replies at heading boundaries measurably helped, but it has never been tested systematically. A chunked node's sibling count in one result is capped, not tuned. conversation turn and doc section both split one reply or file into several nodes; at most 2 of them may appear together in a packed result. Found live: a query for "token" returned 9 of its top 12 hits as different pieces of one heavily-sectioned reply, crowding out the node that actually answered it. The cap of 2 is a judgement call, not a measured optimum, same as the ranking priors' budget above. The size of the prior budget is a judgement call, not a measured optimum. Priors are now bounded jointly rather than one at a time, which closed a real 4× hole see the ranking section , but the 2× budget itself has never been tuned against a labelled relevance set — there isn't one. It is a defensible constant, not a result. What is measured is the direction: on four real queries against this repo's own memory, switching to the joint cap moved the section that answered the question up in three of them the rationale section for "why BM25 before vector search" went from rank 4 to rank 1 and displaced no query's correct top hit. init , sync , query