deja-vu

README

The one memory your coding agents share, built from the history already on your disk.

Your agent is about to re-debug something you fixed in March — in a different agent. deja indexes the sessions Claude Code, Codex, Cursor and every other agent on this machine already wrote to disk, and hands the right one back in whichever agent asks.

_{Nobody searched anything — the agent called deja itself. Every line is quoted from two real sessions.}

Every memory tool starts empty and records forward. deja starts full.

And nobody has to ask for it: recall arrives at session start, on every prompt, before a file is edited or a command runs, and after one fails. Keys and tokens are stripped as the index is built, so what reaches the model is safe to send.

85.3% hit@1 on LongMemEval-S · 69.6% on LoCoMo · millisecond lookups over 5 GB of history
_{Both harnesses ship in this repo and run on the public datasets in minutes · check the numbers yourself}

English | 中文

Docs · Benchmarks · How it compares

Install

curl -fsSL https://raw.githubusercontent.com/vshulcz/deja-vu/main/install.sh | sh
deja install --auto

Ten seconds to install, about ten to index, and it is useful. The second command wires MCP recall into every agent it finds, turns on session-start recall where the agent supports it, and builds the first index so the next session does not pay for it.

Start a new agent session and ask it something you worked on months ago:

have we dealt with jwt refresh rotation before? check your memory

It does not have to be asked, either — with auto-recall the agent already knows what you solved in that project when the session opens.

Other ways to install, and what to do if you want less than all of it

brew install deja-vu, go install github.com/vshulcz/deja-vu/cmd/deja@latest, or npx @vshulcz/deja-vu "query" to try it without installing anything. Desktop apps that take MCP servers as bundles can open the .mcpb from the latest release; it carries the binary.

Claude Code, Codex, Cursor, Qwen, OpenClaw and Copilot can take the same plugin bundle from their own marketplaces instead:

claude plugin marketplace add vshulcz/deja-vu && claude plugin install deja-vu@deja-vu

On Windows the install script exits with unsupported OS — it is a shell script. Use Scoop instead, from the main bucket every Scoop install already has:

scoop install deja-vu

Or take deja-vu_<version>_windows_amd64.zip from the latest release and put deja.exe on your PATH, e.g. in %USERPROFILE%\.local\bin.

The binary alone is a complete install for searching: index, search, show, ctx, blame, --json and redaction need nothing else. deja install is what wires MCP into your agents and turns on session-start recall — worth having, and optional. On a binary-only setup deja doctor reports every MCP target as not-wired, which is that setup working as intended. deja warmup also leaves a skill at ~/.agents/skills/deja-search/SKILL.md that teaches an agent the CLI contract — deja search --json, ctx, blame, how to read tier and total — so it knows history is searchable without MCP. The copy in the repo is skills/deja-search/SKILL.md.

deja install --all is --auto without the session-start recall: agents answer from memory when they decide to call it, rather than starting each session with it. The agent setup guide covers what each harness supports, aider's read-only context file, and the Windows cmd /c deja mcp wrapper.

What gets written into each agent's own guidance file

Install also writes user-level guidance for the harnesses it detects: Claude Code, Codex, opencode, Gemini CLI, Antigravity, Qwen, Kimi Code, pi, Copilot, VS Code Copilot Chat, Cursor, Goose, OpenClaw, Hermes, Roo Code, omp, Amp, DeepSeek Harness and Zed each get it in their own guidance file (or under the configured XDG_CONFIG_HOME). Re-run rewrites deja's skill or marked block without changing surrounding user content. Use deja install --all --no-guidance to opt out; Grok Build gets the shared skill in ~/.agents/skills, which is what it reads; the ~/.grok/GROK.md written beside it is for the unrelated community CLI that shares that directory. Cursor has no user-level instructions file, so it gets a skill at ~/.cursor/skills/ instead, read only when something looks relevant rather than every session.

What you get

Solve it in Codex. Claude remembers. Twenty-three coding agents write every conversation to local files, and deja turns those files into one memory layer all of them read.

Retroactive search	deja "connection pool exhausted" over gigabytes, including everything from before you installed deja. Natural-language questions fall back to a relevance tier. Time is a hint, not a filter.
Cross-agent recall	The MCP recall tool answers "we fixed this three weeks ago" in whichever agent asks, whoever solved it originally.
It survives compaction	Measured over 43 compactions: the summary keeps 77% of the decisions and 0.2% of the commands you ran. deja hands back the other 99.8%.
Recall at the point of action	Before an agent edits a file or runs a command, deja names that file's prior decision or that command's working invocation, from a PreToolUse hook. When a command fails, a PostToolUse hook answers with what followed that same error here before — the pair an agent never thinks to ask for.
It indexes the work, not just the talk	The files each turn opened, the commands that ran with their exit status, and the exact spans an edit replaced. That is the part every summary throws away.

Four more: rejected decisions, staleness, sync and handoff, redaction

It knows what held	deja promote <id> --state rejected --note "why" marks a decision you reverted. Every later hit for that session shows it was tried and rejected, with the reason. Nothing is deleted, and --state accepted takes the mark back.
It says when the ground moved	A hit reports 4 files this session touched have changed since, and says nothing when it cannot tell. It never claims anything is unchanged.
Sync and handoff	deja sync ssh laptop moves memory between machines, append-only, no cloud in the middle. deja handoff --to codex packages the live context so you can continue in another agent.
Redaction	Keys, tokens, JWTs and private key blocks are stripped at index time, so the cache is safe to keep.

Your own work, wrapped

deja stats --card draws it in the terminal; give it a filename and it writes an SVG for a profile README. To post it anywhere else, turn it into a PNG — that page converts it in your own browser.

The full feature reference lives in the docs.

Privacy

Indexing and search are local. The network is used only by deja update, deja sync ssh, and the version check in deja doctor.

Credentials are redacted at index time: AWS keys, api_key= and token= assignments, bearer tokens and raw JWTs, PEM private key blocks, provider tokens, scheme://user:pass@host URLs, and high-entropy values for shapes no pattern knows. The value becomes [redacted:<kind>] and the surrounding text stays searchable. deja share and deja sync export re-apply redaction on the way out.

deja forget removes sessions from a rebuilt index and writes tombstones, so a later deja index cannot restore them from the source history. --unforget lifts a tombstone. Project exclusions are one pattern per line in ~/.config/deja/exclude.

The security model documents data flows, redaction limits, trust assumptions and release verification.

CLI

$ deja "jwt refresh token"
[claude] api        · Jul 8 · 8f31c0a9 — 2 matches
  login started failing after refresh token rotation; jwt kid mismatch in tests
  fixed by reloading jwks cache after rotateKey and adding a clock-skew test
[codex]  web        · Jul 1 · b77d91e2 — 1 match
  refresh token cookie needed SameSite=Lax in local callback flow

Ask your history

Command	What it does
deja <query>	Search every history. Multi-word is AND and quoted phrases require contiguous text; a query with no exact match then tries word forms and close spellings, which is where a substring reaches its word (code finds opencode).
deja	With an index and a terminal: today's sessions, recalls served, a question you asked in more than one session, and a wall your agents keep hitting.
deja blame <path>	Which sessions discussed a file, what was decided, and why.
deja files <topic>	The other direction: which files the work on a subject actually touched.
deja how <tool>	How this machine actually runs a thing, with the real flags, from what agents ran before.
deja fix <error>	What this machine ran after that same error before, when the error did not come back.
deja friction	Errors that hit three or more separate sessions, with the harnesses named.

Using what it finds, and moving it between machines

Use what it finds

Command	What it does
deja ctx <query>	Markdown digest of the best match, ready to pipe into a prompt.
deja resume <id>	Reopen a found session in its native harness.
deja restore <path>	Hand back a span an agent replaced, from the old_string its edit recorded. Never writes over the original.
deja promote <id>	Distill a session into a curated note with provenance, tags and a lifecycle state. Notes outrank raw transcripts.
deja share <id>	A sanitized session digest for a colleague, with secrets already scrubbed.

Move it and check it

Command	What it does
deja sync export/import/ssh	Move memory between machines. Watermarked, append-only, idempotent.
deja view	Your whole memory as one local HTML file. No server, nothing leaves the machine.
deja stats	Your agent work, wrapped. --card draws it in the terminal, --card <file>.svg writes one for a profile, --html a browsable timeline.
deja doctor [--deep]	Self-diagnosis, and with --deep, proof of the index against the sources.
deja mcp	The stdio MCP server, which is what deja install wires in.

Full reference: commands and JSON output.

MCP tools

The server exposes one tool, deja, with a mode. deja install wires it in, so this is only needed to configure an agent by hand. The six older tool names (recall, recall_context, blame, fix, how, remember) still answer for anything already wired to them.

Arguments and return shapes

Tool	Arguments	Returns
deja	mode, plus query, path, error, what, text, tags?, harness?, project?, since?, limit?, offset?, all?	Depends on the mode, below.

Mode	Arguments it reads	Returns
recall	query, harness?, limit?, offset?	Dense matching snippets, capped at 4KB.
context	query, harness?	Markdown digest of the best-matching session.
blame	path, harness?, project?, since?, limit?, all?	Sessions that discussed a file.
fix	error, project?, limit?	What this machine ran, or changed, after that same error before.
how	what, project?, limit?	The real invocation, from what agents ran here.
remember	text, project?, tags?	Stores a durable decision for later recall.

Supported harnesses

aider · Amp · Antigravity · Claude Code · Cline · Codex CLI · Copilot CLI · VS Code Copilot Chat · Cursor · DeepSeek Harness · Gemini CLI · Goose · Grok Build · Hermes · Kimi Code · omp (Oh My Pi) · OpenClaw · opencode · pi · prime-agent (PrimeIntellect) · Qwen Code · Roo Code · Zed.

What each one supports

Harness	MCP recall	Auto-recall	Skill	Command	Resume	Handoff	Needs
aider	⚠	✅	✕	⚠	✕	✅	deja aider
Amp	✅	✅	✅	✅	✅	✅	—
Antigravity	✅	✅	✅	✅	✅	✅	—
Claude Code	✅	✅	✅	✅	✅	✅	—
Cline	✅	✅	✅	✅	✅	✅	—
Codex CLI	✅	✅	✅	✅	✅	✅	—
Copilot CLI	✅	✕	✅	✅	✅	✅	—
VS Code Copilot Chat	✅	✕	✅	—	✕	paste	—
Cursor	✅	✅	✅	✅	✅	✅	sqlite3 (IDE chats)
DeepSeek Harness	✅	✅	✅	✅	✕	paste	zstd
Gemini CLI	✅	✅	✅	✅	✅	✅	—
Goose	✅	✅	✅	✅	✅	✅	deja goose
Grok Build	✅	✅	✅	✅	✅	✅	sqlite3 (grok-dev store)
Hermes	✅	✅	✅	✅	✅	paste	sqlite3
Kimi Code	✅	✅	✅	✅	✅	✅	—
omp (Oh My Pi)	✅	✅	✅	✅	✅	✅	—
OpenClaw	✅	✅	✅	✅	✅	paste	—
opencode	✅	✅	✅	✅	✅	✅	sqlite3
pi	✅	✅	✅	✅	✅	✅	—
prime-agent (PrimeIntellect)	—	—	—	—	—	paste	—
Qwen Code	✅	✅	✅	✅	✅	✅	—
Roo Code	✅	⚠	✅	✅	✕	paste	—
Zed	✅	✕	✅	✅	✕	paste	sqlite3 + zstd

✅ works · — possible, not built yet · ✕ the harness has no such mechanism · ⚠ blocked by an upstream bug · ? not investigated

Custom store locations go through DEJA_*_ROOT variables, and each agent's own relocation variable is honored too. The session format registry documents the observed paths, record schemas and role mapping per harness, with synthetic fixtures keeping those descriptions checked against the parsers.

Harnesses with a package of their own

deja install --auto wires all six of these like every other harness, and that stays the shortest path. They also have a package in their own ecosystem, for people who install extensions there rather than from a CLI:

Harness	Package	Install
opencode	npm opencode-deja	opencode plugin opencode-deja
DeepSeek Harness	npm dsh-deja	dsh plugin --profile web add dsh-deja
Zed	deja-context-server	Zed → Extensions → deja
Kimi Code	plugin deja	/plugins install https://github.com/vshulcz/deja-vu
Codex CLI	plugin deja-vu	codex plugin marketplace add https://github.com/vshulcz/deja-vu then codex plugin add deja-vu@deja-vu
Grok Build	plugin deja	grok plugin marketplace add xai-org/plugin-marketplace then grok plugin install deja

Either path is enough on its own, and having both is not a problem: the opencode, dsh, Kimi, Grok and Codex packages read what deja install wrote and contribute only what is missing, and in Zed both halves use one server id, so there is nothing to have twice whichever order you install in.

Each uses the deja you already have; the copy it bundles is only the fallback.

The same search is also a skill, for any agent that loads a SKILL.md:

npx skills add https://github.com/vshulcz/deja-vu --skill deja-search   # skills CLI: Claude Code, Cursor, Goose, Copilot…
openclaw skills install @vshulcz/deja-search                            # ClawHub
hermes skills install vshulcz/deja-vu/skills/deja-search                # Hermes

The skill drives the deja binary from the install step above; it does not bundle one.

Semantic recall (optional)

Point deja embed at a local Ollama, LM Studio or OpenAI-compatible endpoint with DEJA_EMBED_URL and rephrased queries still hit. Without a reachable runtime, lexical search and MCP recall continue unchanged. OpenAI Platform works with its standard key:

export OPENAI_API_KEY='sk-...'
export DEJA_EMBED_URL='https://api.openai.com/v1/embeddings'
export DEJA_EMBED_MODEL='text-embedding-3-small'
deja embed

With no DEJA_EMBED_URL set, deja probes localhost:11434 and localhost:1234, so a machine already running Ollama or LM Studio is picked up without being asked. DEJA_EMBED_OFF=1, or DEJA_EMBED_URL=off, turns that probe off — any other configured DEJA_EMBED_URL still wins.

For another authenticated OpenAI-compatible endpoint, set DEJA_EMBED_KEY explicitly:

export DEJA_EMBED_URL='https://example.com/v1/embeddings'
export DEJA_EMBED_MODEL='embedding-model'
export DEJA_EMBED_KEY='...'
deja embed

DEJA_EMBED_KEY takes precedence. OPENAI_API_KEY is used automatically only for an HTTPS api.openai.com URL; it is never implicitly sent to local or third-party endpoints.

Where the vectors live and what they cost

The sidecar sits beside the index as .vectors.bin, not inside index.db. Float32 vectors cost roughly 4 MB per 1k messages for a 1,024 dimension model. A remote endpoint receives the redacted indexed text, truncated to about 2k characters, but never raw source files. With Ollama or LM Studio, embedding stays local and needs no key.

Proof

deja bench recall     # ranking regression floor, CI fails if recall drops
deja bench context    # 30 seeded task chains plus five negative controls
deja bench block      # does the answer survive into what deja hands over

bench block asks the question the other three cannot: with the right session in hand, does the block carry what that session settled. Eight sessions discuss each subject and one of them settles it, in the middle of its own transcript rather than at the end — so the baseline arm, the newest turns of the top hit, scores zero and an arm above zero had to choose.

Arm	Carries the answer	Median tokens
deja-block (session-start block)	1.00	665
deja-digest (context digest)	1.00	1656
newest-turn (baseline)	0.00	289
cold	0.00	0

The context experiment compares deja-recall against full-history, naive grep and cold context. With the default seed:

Arm	Median tokens	Median coverage	Negative-control tokens
deja-recall	286	1.00	0
full-history	16,919	1.00	14,920
naive-grep	57,489	1.00	0
cold	0	0.00	0

Same fact coverage as grepping the raw logs for about 200x fewer tokens, and about 60x fewer than replaying the matched sessions in full, while injecting nothing on the chains where no prior fact is relevant. The corpus generator and the relevance labels are ordinary reviewed Go. Audit what "relevant" means before trusting any figure, ours included.

Measured on a real store of 1,551 sessions and 143k messages — 5.2 GB across nine harnesses:

Measurement	Result
Lookup, in process	~0.4 ms median (deja bench recall), ~25 ms on the LongMemEval-S haystacks
deja <query>, end to end	~0.2 s median on that store: process start, the freshness check over every store, ranking, printing
Freshness check alone	~30 ms when nothing changed
Index size	160 MB, ~3% of corpus

The index is incremental. When a session file grows, only that file is re-read.

How it works

Local inverted index in ~/.cache/deja: parse the JSONL and SQLite stores, redact credentials, write records.bin plus token buckets, and track per-file state in manifest.gob so repeat runs only ingest what changed. The MCP server, stats, share and sync all read that one index. Details in docs/ARCHITECTURE.md.

FAQ

Does anything leave my machine? No, unless you ask it to. See the data flows.

What about secrets already in my logs? They stay in the original harness files, which are your agent's data. Known shapes — AWS keys, api_key=/token= assignments, bearer tokens and bare JWTs, PEM blocks, provider tokens, high-entropy values — are stripped as the index is built, so they do not reach digests, shares or sync exports. Pattern matching is not secret detection: a shape it does not know can pass through. See the security model.

Will it slow my agent down? A recall is a lexical lookup against a local index: ~0.4 ms median, and nothing waits on a model. A hook adds the process start and a freshness check over your stores on top of that — tens of milliseconds on a store of a few gigabytes.

Do I have to change how I work? No. The agent calls recall itself, and with auto-recall it already knows the project's prior decisions when the session opens.

How is this different from the other memory tools?

	deja	Memory platforms (Mem0, Letta, memU)	Session search (cass)
Knows work from before you installed it	yes	no	yes
Capture step	none, the transcripts are the memory	the agent or your code writes facts	none
Needs an LLM or embedding key	no	yes	optional
Recalls without being asked	at session start and before a tool runs	no	no

engram is the strongest of the record-forward tools and worth your time if that model fits you; it still starts empty and knows only what an agent chose to save. The full comparison covers eleven of them.

Where is Claude Code session history stored, and can I search it? Under ~/.claude/projects, one JSONL file per session; Codex keeps ~/.codex/sessions, Cursor a SQLite state.vscdb. deja search reads them all in place, deja last lists the recent sessions of every agent, and deja view opens the whole history as one local page. Paths for each agent: where sessions are stored.

My Claude Code session history disappeared. Is it gone? Claude Code deletes transcripts older than 30 days (cleanupPeriodDays in ~/.claude/settings.json), and claude --resume lists only what is left. A session deja indexed before the cleanup stays searchable after the file is gone. Details: session files on disk.

What about Windows? Builds exist and CI runs the suite there. macOS and Linux are the battle-tested paths. Field reports welcome in #9.

How do I wipe everything?

deja uninstall --all
rm -rf ~/.cache/deja

Guides

Written for the situation rather than the feature:

• Does your agent remember previous conversations? — what each agent keeps between sessions, and what it drops
• Session files on disk — how big ~/.claude/projects gets, and what deleting it costs
• The agent lost the context you had — after a crash, a clear, or a session that came back empty
• The context window is full — what compaction keeps, measured, and what to do instead
• Resuming yesterday's session — find it across every agent, reopen it in the one that owns it
• The agent repeats a mistake you already fixed
• Finding the session where you solved it
• Why agents forget between sessions · Where each agent keeps its history
• What compaction drops · Switching agents · Auditing an agent · Exporting a conversation · Across machines · What memory costs

Per harness: opencode · DeepSeek Harness · Kimi Code · Zed · Grok Build · Gemini CLI · Qwen Code · OpenClaw · Goose · Cline · pi and omp · Hermes

Try it on your own history

curl -fsSL https://raw.githubusercontent.com/vshulcz/deja-vu/main/install.sh | sh
deja install --auto

Ten seconds to install, about ten to index. The next session your agent opens, it already knows what you solved in that project — including everything from before you installed this.

Contributing

make build test lint, then CONTRIBUTING.md. Adding a harness starts in the parser registry. Priorities and non-goals are in ROADMAP.md. Good first issues are labeled.

License

MIT © Vladislav Shulcz