Your coding agents stop re-debugging what you already fixed.
Claude Code, Codex, Cursor, OpenClaw, Gemini CLI, OpenCode, Hermes and 36 more agents already save every session to disk.
deja indexes all of it locally and hands the relevant history back over MCP and hooks — no LLM, one Go binary.
deja with no arguments opens a terminal search across every agent's history — starting with
the sessions behind your uncommitted changes, then recent work in the current project.
Navigate:↑↓ picks a session, ↵ opens at the match, / searches inside a session, ][ jump between turns, ^s toggles date/relevance sort (deja search --sort date).
Filter: by agent (codex:), time (today, yesterday, week, month), or project (in:<project>).
Resume or hand off:r reopens the session in its native agent; o continues it in another agent with its goal, decisions and open work.
Recover deleted chats:tab switches between this project, all projects, and Deleted (sessions an agent purged that deja still holds); R restores one, D deletes (deja delete <id>), ? lists all keys.
Prefer a browser? deja view exports the store — sessions, the recall audit trail, and promoted notes — into one local HTML file (try the live demo). With DEJA_TUI=0 (or deja brief), deja prints a plain-text summary.
Highlights
Starts full on day one. Months of existing transcripts across all forty-three agents are searchable immediately — fix a bug in Codex and Claude Code, Cursor or OpenCode recalls it.
Automatic recall via hooks & MCP. Surfaces prior sessions at session start, before a file edit or command runs, and when a command fails.
Survives compaction. Over 43 measured compactions, summaries kept 77% of decisions and 0.2% of commands; deja hands back the rest (how).
Indexes code changes, not just chat. Tracks opened files, commands with exit codes, and exact Edit spans (deja blame <file>:<line>, deja restore <path>).
Tracks decision lifecycle & staleness.deja promote <id> --state rejected marks a reverted approach so later hits warn why it was dropped (--state accepted takes the mark back), and hits report when files touched by a session have changed since.
Local and private by default. Zero LLM calls, no cloud account, and automatic credential redaction at index time (privacy).
Your own work, wrapped
deja stats --card draws your yearly agent activity in the terminal or writes an SVG for your GitHub profile (convert to PNG in browser).
install.sh places the deja binary in ~/.local/bin, and deja install --auto wires MCP recall and hooks into every detected agent and builds the initial index (~10s).
Open a new session in any wired agent and it already knows what you solved in that repository — or ask it directly (have we dealt with jwt refresh rotation before?).
Homebrew, Windows (Scoop / winget), npm, plugin marketplaces, and binary-only setup
brew install deja-vu, nix run github:numtide/llm-agents.nix#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.
Codex CLI, opencode, Claude Code, Qwen and OpenClaw can also install the plugin
bundle directly from their own marketplaces or registries (see
Harnesses with a package of their own,
plus cursor-plugin/ for Cursor). Copilot CLI installs the
marketplace bundle too, though it takes only the skill there — use
deja install copilot-auto for hooks and MCP:
On Windows the install script exits with unsupported OS — it is a shell script. Use
Scoop, from the main bucket every Scoop install already has, or winget, which ships with Windows:
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 config missing, or not-wired where the agent
is installed, 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 recall, ctx, , how to read the
recall page and ask for the next one — so it knows history is searchable without MCP. The copy in the repo is
.
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, Senpi, Copilot, VS Code Copilot Chat, Goose, OpenClaw, Hermes, Roo Code, omp, Amp, prime-agent, DeepSeek Harness, Continue, Crush, CodeBuddy Code, WorkBuddy, Zed, TRAE CLI, TRAE IDE, Muse Code, CodeWhale, ZCode and Junie 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 and Devin CLI get the shared skill in ~/.agents/skills, which is what they read; 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 the shared skill in ~/.agents/skills — one of the four places Cursor reads skills from — read only when something looks relevant rather than every session. Kilo Code, gajae-code, Kimchi, Command Code, Cherry Studio and Reasonix get the skill, MiniMax Code gets it inside the plugin package, and Kiro the skill and a steering file, from their own install target.
Privacy
Indexing and search are local. The network is used only by deja update, deja sync ssh,
the version check in deja doctor, deja embed against an endpoint you configure (and,
once it has built the semantic sidecar, each search, which sends the query to that
endpoint), and a once-a-day look at the latest release from an interactive command. That look sends no
session data; DEJA_OFFLINE=1 turns it off, and so does DEJA_NO_UPDATE_NOTICE set to any
value, which also hides the note a new version prints on its first run.
Credentials are stripped as the index is built: cloud and provider keys, tokens and JWTs,
PEM blocks, passwords in URLs or stated in prose. Each becomes [redacted:<kind>] and the
text around it stays searchable. The source transcripts still hold them
(one machine had 84 in 42 sessions):
deja secrets names those sessions without printing a value, and deja secrets --scrub
rewrites the ones it can, keeping the original beside the file.
deja forget drops sessions and keeps them dropped across rebuilds. ~/.config/deja/exclude
skips a project per line, or a whole store with harness:opencode. The
security model has the data flows and what redaction cannot catch.
CLI
Bare deja in a terminal opens the search screen. With a query,
or any command below, it prints and exits:
$ 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). --sort date lists the newest match first.
deja
In a terminal, the full-screen search above. deja brief prints the text summary instead: today's sessions, what deja served, recent work and a search to try.
deja wip
What the last session in this directory was doing: the task, what it settled, the files in flight, the last command and whether it failed — derived from the transcript, not from a note someone remembered to write.
deja blame <path>[:line]
Which sessions discussed a file, what was decided, and why. With a line: the commit that last changed it, and the session that wrote that line or the text the commit replaced. --attribution prints the line answer alone, as JSON with --json, and --git-note records it in refs/notes/deja.
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. Never a merge, a force push or a deletion.
deja friction
Errors that hit three or more separate sessions, with the harnesses named.
When the first word of a bare query has at least four characters and is one
edit from a command name, deja names that command on stderr and then searches
as usual. deja search <query> skips the suggestion.
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, with the code it changed, ready to pipe into a prompt.
deja recall <words>
The page the MCP recall tool gives an agent: about 4 KB, this project first (DEJA_RECALL_GLOBAL=1 ranks every project the same). For skills and scripts that run deja through the shell.
deja resume <id>
Reopen a found session in its native harness. --app opens a Codex session in the ChatGPT desktop app.
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 (live demo). No server, and the file never 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 secrets [--scrub]
Which sessions' source transcripts carry credentials, and what kind. Never prints a value. --scrub rewrites the ones it can, original kept beside the file.
deja rules [sync]
Keep your standing rules in ~/.config/deja/rules.md; sync copies them as a marked block into every installed agent's global rules file.
The server exposes one tool, deja, with a mode; deja install wires it in. One tool
costs 477 tokens of definitions a turn, against 8,283 for the largest of the seven servers
measured in day zero. The six
older tool names (recall, recall_context, blame, fix, how, remember) still answer.
deja mcp --context-search is a separate server with a single context_search tool, for
Qwen Code's External Context MCP Profile v1 (Qwen page).
Arguments and return shapes
Tool
Arguments
Returns
deja
mode, q, harness?, project?, limit?
Depends on the mode, below.
q carries whatever the mode asks about. The per-mode names below are still
accepted; they are no longer declared, because the schema is read every turn
whether or not the tool is called.
Mode
q is
Also reads
Returns
recall
1-3 exact terms: a file path, an error string, a flag or identifier
harness?, limit?, offset?
Dense matching snippets, capped at 4KB.
context
the same as recall
harness?
Markdown digest of the best-matching session, with the code it changed.
blame
a file path
harness?, project?, since?, limit?, all?
Sessions that discussed a file.
fix
the failing output, verbatim
limit?
What this machine ran, or changed, after that same error before.
how
the tool or target, e.g. go test
project?, limit?
The real invocation, from what agents ran here.
orient
nothing — it asks about the project
project?, limit?
The commands past sessions ran here and the files they worked in.
remember
one durable fact or decision
project?, tags?
Stores a durable decision for later recall.
handoff
a session id or harness name; empty for the newest session here
threads from 0.0.1774963753 on live on ampcode.com; deja reads those its plugin has written out, and older local ones
Antigravity
✅
✅
✅
✅
✅
✅
—
Claude Code
✅
✅
✅
✅
✅
✅
—
Cline
✅
✅
✅
✅
✅
✅
—
Codex CLI
✅
✅
✅
✅
✅
✅
—
Copilot CLI
✅
✅
✅
✅
✅
✅
—
TRAE IDE is wired, not read: its chats are in an encrypted database. deja install trae-ide
adds the MCP server and the skill, and trae-ide-auto adds hooks, which TRAE IDE runs only
after you turn them on in Settings > Hooks.
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 every one 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:
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
Local runtimes, other endpoints, and what vectors cost
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.
Models trained with instruction prefixes, such as the multilingual E5 family, need them on
both sides. DEJA_EMBED_QUERY_PREFIX goes in front of every search query and
DEJA_EMBED_PASSAGE_PREFIX in front of every indexed text; both are empty by default:
export DEJA_EMBED_MODEL='multilingual-e5-small'
export DEJA_EMBED_QUERY_PREFIX='query: '
export DEJA_EMBED_PASSAGE_PREFIX='passage: '
deja embed
The passage prefix is part of the sidecar's model name, so changing it embeds everything
again, and search ignores vectors made with another model or prefix (it says so once).
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
Millisecond lookups, and on LongMemEval-S 88.9% hit@1 (470-question cleaned set) and 88.2% hit@1 on all 500 questions;
on LoCoMo retrieval, 71.9% hit@1. On a task this machine had already solved, 58% fewer
tokens: eleven runs an arm, 53,558 against 126,222 with nothing wired, and 52,815 against
103,443 on a later build with the arms alternated. Both retrieval harnesses ship in this repo
and run on the public datasets in minutes: benchmarks ·
what one task costs.
The rest is measured by deja bench:
deja bench recall # ranking floor: 100 queries, half Russian, 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
deja bench prompt # what the per-prompt hook fires on, and what it fires on wrongly
deja bench ingest # what an update costs: unchanged, a turn, a new transcript, a rename, a rewrite
deja bench read # what it costs to read a database-backed store, and what one long value does to it
What the in-repo benches measure, and lookup cost on a real store
bench block asks the question the others 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
1,096
1.00
0
full-history
80,547
1.00
78,145
naive-grep
273,238
1.00
0
cold
0
0.00
0
Same fact coverage as grepping the raw logs for about 250x fewer tokens, and about 70x
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 2,419 sessions and 179k messages, 1.9 GB of
transcripts:
Measurement
Result
Lookup, in process
0.7–0.8 ms median (deja bench recall, 100 queries, half of them Russian), ~15 ms on the LongMemEval-S haystacks
How it works
Local inverted index in ~/.cache/deja: parse the JSONL and SQLite stores, redact
credentials, write an append-only 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
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 15 of them.
Will it slow my agent down?
A recall is a lexical lookup against a local index:
0.7–0.8 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: about 0.2 s end to end on a 1.9 GB
store. On an index of 19k sessions the per-prompt hook takes 107 ms at the median,
and a recall through deja mcp 85 ms.
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 reads them all in place: bare deja opens a screen to search
and read them, deja search does it from a script, 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, and the weekly note at session start says how many it kept, with an id
deja resume <id> --write-back puts back. Details: session files on disk.
Can I stop it reindexing on its own, or index for search only?
Yes. DEJA_NO_AUTO_INDEX=1 or "auto_index": false in ~/.config/deja/policy.json stops every automatic update; search, MCP recall and hooks answer from the last finished index.
DEJA_SEARCH_ONLY=1 or "search_only": true in ~/.config/deja/policy.json skips mining fixes, commands and co-occurrence (~20% of a build's CPU). The DEJA_INDEX_* switches that keep commands, tool output, paths and edits out of the index are in the commands guide.
One project is spread over several checkouts. Can recall treat them as one?
List the trees in ~/.config/deja/projects, one <path> = <name> per line:
~/work/monorepo = work
~/work/worktrees = work
Every directory under a listed path is then that project, for indexing, the hooks and recall alike; the longest matching path wins. Run deja index --rebuild to re-file existing transcripts under the new name. The exclude file still wins over project aliases.
How do I wipe everything?
deja uninstall --all
rm -rf ~/.cache/deja ~/.local/share/deja ~/.config/deja
The index is under ~/.cache/deja, your remember and promote notes in
~/.local/share/deja, and the rules, exclude list, project aliases and hook launcher in
~/.config/deja (or under XDG_DATA_HOME and XDG_CONFIG_HOME when set; on
Windows the notes are in %AppData%\deja).
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.
Support
Bugs and questions go to issues.
Anything you think is exploitable goes through the private advisory link in
SECURITY.md instead. What deja reads, what it never sends
anywhere, and how to exclude a project or forget a session is under
Privacy. Found it useful? Star deja-vu on GitHub.
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.
deja rules candidates [--json] [--limit n] [--since 90d]
The turns where you corrected an agent, across every tool, numbered with their session. Ask your agent to suggest rules and it groups them; nothing is written until you pick.
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.
Another session's goal, standing instructions, latest conclusions, passed checks and where it stopped, to continue it.
VS Code Copilot Chat
✅
✅
✅
✅
✕
✅
—
Cursor
✅
✅
✅
✅
✅
✅
sqlite3 (IDE chats, CLI tool output)
DeepSeek Harness
✅
✅
✅
✅
✕
✅
zstd
Gemini CLI
✅
✅
✅
✅
✅
✅
—
Goose
✅
✅
✅
✅
✅
✅
deja goose
Grok Build
✅
✅
✅
✅
✅
✅
sqlite3 (grok-dev store)
Hermes
✅
✅
✅
✅
✅
✅
sqlite3
Kimi Code
✅
✅
✅
✅
✅
✅
—
omp (Oh My Pi)
✅
✅
✅
✅
✅
✅
—
OpenClaw
✅
✅
✅
✅
✅
✅
sqlite3 (2026.8+ store); zstd for .zst archives and compressed events (2026.9.9+)
opencode
✅
✅
✅
✅
✅
✅
sqlite3
Continue
✅
⚠
✅
✅
✅
✅
—
Crush
✅
✅
✅
✅
✅
✅
sqlite3
pi
✅
✅
✅
✅
✅
✅
—
prime-agent (PrimeIntellect)
✅
✅
✅
✅
✅
✅
—
Qwen Code
✅
✅
✅
✅
✅
✅
—
Cherry Studio
✅
✅
✅
✕
✕
paste
import the server once in Settings -> MCP; enable the skill for the agent
Senpi
✅
✅
✅
✅
✅
✅
none
gajae-code
✅
✅
✅
✅
✅
✅
none
Kimchi Coding
✅
✅
✅
✅
✅
✅
none
Command Code
✅
✅
✅
✅
✅
✅
none
ZCode
✅
✅
✅
✅
✅
✅
sqlite3 for the CLI database
Kiro
✅
✅
✅
✅
✅
✅
sqlite3 for the CLI database
Kilo Code
✅
✅
✅
✅
✅
✅
sqlite3 for the CLI store
Roo Code
✅
✕
✅
✅
✅
paste
roo CLI (editor tasks reopen in the editor)
Zed
✅
✕
✅
✅
✕
paste
sqlite3 + zstd
Devin CLI
✅
✅
✅
✕
✅
✅
sqlite3
CodeWhale
✅
✅
✅
✅
✅
✅
none
Junie
✅
✅
✅
✅
✅
✅
none
JetBrains AI Assistant
✅
⚠
⚠
⚠
✕
paste
none
Windsurf / Devin Desktop
✅
⚠
✅
✅
✕
paste
none
CodeBuddy Code
✅
✅
✅
✅
✅
✅
none
Reasonix
✅
✅
✅
✅
✅
✅
zstd for 1.x sessions
TRAE CLI
✅
✅
✅
✅
✅
✅
none
Muse Code
✅
✅
✅
✅
✅
✅
none
MiniMax Code
✅
✅
✅
✕
✅
✅
the MiniMax Code CLI (mcode) for deja resume and deja handoff --to mcode --exec; sqlite3 for the session's workspace
✅ works · — possible, not built yet · ✕ the harness has no such mechanism · ⚠ waiting on the harness itself · ? not investigated
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
~50 ms when nothing changed
Index size
200 MB, ~10% of corpus
The same store has since grown to 2,754 sessions, 358k messages and 5.7 GB.
A cold full build over it takes 71 s and writes a 232 MB index — 4% of the
corpus, because the share falls as transcripts repeat themselves — and the
end-to-end median is unchanged at 0.25 s. Since 0.23.2 records are compressed
from 256 bytes, which takes a 19k-session index from 277 to 185 MB.
The index is incremental. When a session file grows, only that file is re-read. When one is
rewritten, its new records are appended and the old ones zeroed in place. On a
40,000-session store a pass over 20 rewritten transcripts takes 1.7 s and peaks under 1 GB,
and a search for a word most sessions hold takes about a second.
