session-recall
The session-recall server provides tools to semantically search, navigate, and grep through past Claude Code and Codex conversations, offering shared memory across AI engines.
recall_search(query)— Semantically search past sessions by meaning (not just keywords). Returns ranked anchors with relevance scores and timestamps. Optionally scope to the current repo (scope_cwd), filter by source (claude/codex), or constrain to a date range.expand_around(session_id, uuid)— Retrieve raw turns surrounding a specific anchor, including tool calls, tool outputs, and reasoning/thinking blocks. Configurable number of turns before/after the anchor.step(session_id, uuid, direction)— Walk forward or backward through turns in a session from a given position, acting as a cheap cursor for navigating transcript context.grep(pattern)— Substring scan over all raw indexed transcripts, including under-the-hood turns (tool outputs, thinking) not in the search index. Can be scoped to a session or repo; requires no embedding API key.recent_sessions()— List the most recently active sessions in reverse chronological order, showing session ID, project, turn count, last activity, and opening prompt. Supportsscope_cwdand date filters.
Additional capabilities include automatic incremental indexing of transcripts, date-based filtering with timezone support, and pluggable embedding providers (including local options like Ollama).
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@session-recallRecall what we discussed about error handling last week."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Shared semantic memory for Claude Code, Codex, and Cursor. Find an old decision by meaning. Open the raw evidence. Continue the work.
English · Русский · Español · 中文
Your coding agents remember the current chat. Your work lives across months of chats — resumed sessions, parallel subscriptions, worktrees, different agents.
Session Recall turns that history into one local-first index and serves it back through five focused MCP tools. A fresh session can recover what Codex worked out yesterday and what Claude Code rejected three months ago — with links back to the actual turns, tool output, and reasoning. Not a summary file someone maintains by hand: the original conversation stays the source of truth.
you: we were fixing the auth token conflict between the two services — where did we land?
agent: (recall_search → expand_around) Both services shared one OAuth account, and the provider rotates refresh tokens per account, so each refresh invalidated the other's copy. You rejected the shared-credentials-directory patch as too coupled, and settled on a keeper service owning the session. The spec was never written — that was the next step.
What you get
Capability | What it changes | |
One memory | Claude Code, Codex, and Cursor feed the same index | Switch agents without resetting the project story |
Semantic retrieval | Search by meaning, not only exact words | Recover decisions you can describe but cannot quote |
Deep navigation | Open raw turns: tool calls, outputs, reasoning | Verify the answer instead of trusting a summary |
Honest degradation | A semantic outage is reported explicitly | A literal-only fallback never poses as semantic search |
Local by default | Bundled ONNX embeddings and local SQLite | Start without a key, a server, or an account |
Scoped recall | Filter by repo, source, or local calendar dates | Keep unrelated projects out of the answer |
Team answers | Ask a colleague's local memory, owner-approved | Share hard-won context without exposing raw sessions |
Related MCP server: claude-kb
Where it pays off
Session onboarding. A fresh session starts already in context — whether you juggle several subscriptions, hop between agents, or return to a task you "discussed at some point".
Bugs and regressions. Before fixing anything, the agent asks the history: was this bug seen before? how was it fixed? why did we believe it was fixed? A recurrence stops looking like a fresh bug — and the fix turns from a patch into a dig into the component.
Procedures. Explain a workflow once — how to read a trace, how to break down token spend per task — and any later session replays it without being walked through again.
Cause and effect. Say "let's change this decision", and the agent looks up the moment it was made: "we picked X for compatibility with Y — before changing anything, make sure Y survives."
Five tools, one workflow
The interface stays deliberately small:
MCP tool | Use it when |
| You remember the idea, not the wording |
| You found an anchor and need the surrounding evidence |
| You need the adjacent raw turn without another search |
| You know an exact error, symbol, path, or identifier |
| You want the freshest work — and the index freshness |
flowchart LR
Q["describe the old problem"] --> S["recall_search"]
X["exact error / symbol / path"] --> G["grep"]
S --> A["anchor: session + turn"]
G --> A
A --> E["expand_around"]
E <--> T["step next / prev"]
E --> V["grounded answer + raw evidence"]
R["what is current?"] --> RS["recent_sessions"]Every discovery tool accepts an optional source (claude | codex | cursor), a
scope_cwd to narrow results to the current repo (worktrees collapse to the repo root), and
local calendar dates (on_date, or start_date / end_date, plus an IANA timezone).
Ranked anchors carry provenance and a human-readable timestamp. grep scans all indexed
transcripts on demand — including under-the-hood turns (tool output, thinking) that never
became search chunks. On-demand only: no proactive context injection into every prompt.
{
"query": "why did refresh tokens conflict?",
"scope_cwd": "/work/keeper",
"source": "codex",
"start_date": "2026-05-01",
"end_date": "2026-06-30",
"timezone": "Europe/Moscow"
}recall_search answers {"anchors": [...], "degraded": null | "reason"}. When degraded
is set, the embedding provider was unreachable and only literal matching ran — the agent can
say so instead of mistaking a lexical miss for an empty history.
Quick start
Two pieces: a Python CLI (which also ships the MCP server) and a plugin that wires it into your agent. Budget about two minutes plus the first index run.
1. Install the CLI and build the index
pipx install git+https://github.com/AbsoluteMode/session-recall
session-recall setup # one question (interaction language), then the first indexNo key required: with nothing configured, indexing runs on a bundled CPU model, downloaded
once and picked by your interaction language. The first run walks your whole history —
minutes for months of transcripts, seconds after that. Scripted installs:
session-recall setup --lang en --yes.
$ session-recall index
indexed 2175 chunks from changed transcripts
your history: 1053 sessions spanning 168 days, 40,037 searchable fragments
Claude Code 372 · Codex 680 · Cursor 1
busiest: sidekey, trend_detection, glitchHosted Voyage embeddings rank noticeably better than the bundled model; to use them, export
VOYAGE_API_KEY before indexing — see Embedding providers.
2. Connect your agents
pipx puts session-recall and session-recall-mcp on ~/.local/bin — exactly where the
plugin manifests look for them.
/plugin marketplace add AbsoluteMode/session-recall
/plugin install session-recallThen start a new session — MCP servers, skills, and the SessionStart hook load at session
start, not on install. Prefer to let the agent finish the job? Say set up session-recall
(or run /session-recall:setup): it asks the onboarding questions in chat, runs the
commands itself, and ends with a health check and a real search over your history.
The repository ships a native .codex-plugin/plugin.json —
ready to drop into a local repo or your personal marketplace; see the
local plugin installation guide.
Codex also asks you to review newly installed hooks once via /hooks.
Requires Cursor 2.5+ (plugins were introduced there). Add the repository as a marketplace:
cursor-agent plugin marketplace add https://github.com/AbsoluteMode/session-recall.gitThen type /add-plugin session-recall in Cursor Agent and approve the local stdio MCP
server once, so the tools can start. For plugin development, launch
cursor-agent --plugin-dir /absolute/path/to/session-recall instead of installing a
cached copy.
Cursor is auto-detected at its normal macOS/Linux data path and does not need to be
running. Portable or custom profile? Point at the database directly with
SESSION_RECALL_CURSOR_DB=/path/to/User/globalStorage/state.vscdb.
3. Check it works
session-recall search "something you actually discussed last week"Hits with a score mean semantic search is live. In the agent, claude mcp list should
show session-recall ✔ Connected, and asking about past work should trigger
recall_search. Nothing else to configure: each plugin ships its host's startup hook and
re-indexes in the background, so the shared index keeps up with all three histories on its
own.
How it works
flowchart TB
subgraph Sources["local history sources"]
CC["Claude Code JSONL"]
CX["Codex JSONL"]
CU["Cursor SQLite"]
end
CC --> I["incremental indexer"]
CX --> I
CU -->|"consistent WAL snapshot"| I
I --> V["conversation surface → embeddings"]
I --> R["raw trace, kept local"]
V --> DB["SQLite · sqlite-vec KNN · FTS5"]
R --> DB
DB --> MCP["five on-demand MCP tools"]
MCP --> A["Claude Code · Codex · Cursor · any MCP client"]Only the conversation "surface" is embedded — user prompts and assistant text replies. Tool
calls, results, reasoning, and other trace data are never sent to an embedding provider but
stay reachable on demand via expand_around, step, and grep. Claude sidechains and
spawned-subagent sessions are intentionally skipped: under-the-hood tooling, not the
conversation.
Cursor is read from its SQLite store with the online backup API, so a live WAL database is captured consistently without blocking the editor. Its bubbles are normalized into durable, content-addressed JSONL snapshots under the data directory — deep navigation keeps working after Cursor closes, upgrades, or is uninstalled.
Indexing is incremental and cheap on live transcripts: they are append-only, so unchanged chunks are matched by content hash and their vectors reused — only new turns hit the embedding provider. Moving a Codex rollout into the archive also reuses its vectors. Each file indexes in its own transaction; a failing file is logged and retried next run, never aborting the rest.
CLI cheat sheet
# Refresh every history, or one source
session-recall index
session-recall index --source cursor
# Semantic search — unified by default, scopable to a repo
session-recall search "why did we choose the keeper service?"
session-recall search "deployment work" --source codex --scope /work/keeper
# Local calendar dates, any IANA timezone (defaults to this computer's)
session-recall recent --date 2026-07-14
session-recall search "deployment work" \
--start-date 2026-07-14 --end-date 2026-07-16 \
--timezone Asia/Yekaterinburg
# Exact raw scan — no embedding call, caps at 100 matches by default
session-recall grep "invalid_grant" --limit 100
# Housekeeping
session-recall prune # drop rows for transcripts deleted from disk
session-recall health # the whole chain, verdict GREEN/AMBER/REDsearch, recent, grep, and prune all take --source claude|codex|cursor; omit it for
the unified history. Date filters are inclusive and either boundary may be omitted.
Embedding providers
Nothing is locked to one vendor. SESSION_RECALL_EMBED=<preset> sets endpoint, model,
dimension, and reranker together, because those four are not independent choices:
Preset | Runs | Model | Dim | Reranker |
| bundled, free |
| 384 | — |
| bundled, free |
| 512 | — |
| bundled, free |
| 384 | — |
| local, free |
| 768 | — |
| local, free |
| 768 | — |
| hosted, needs a key |
| 1024 |
|
| hosted, needs a key |
| 1024 | — |
With no preset set, Session Recall picks Voyage when VOYAGE_API_KEY is present, then
probes for a local server already listening, and otherwise runs the bundled ONNX model —
out of the box always works. The bundled flavor follows the interaction language you chose
at onboarding (SESSION_RECALL_LANG=en|zh|…: a small English or Chinese specialist,
multilingual otherwise). First use downloads the model once into the data dir (70–240 MB),
CPU inference from then on. Ranking is noticeably coarser than hosted Voyage — a starting
point, not the ceiling. Local presets ship no reranker, so ranking is KNN + FTS only.
Free and local, start to finish:
ollama pull nomic-embed-text
export SESSION_RECALL_EMBED=ollama
session-recall indexYour own endpoint — any server speaking /v1/embeddings (llama.cpp, vLLM, a company
gateway). Individual variables always beat the preset, so mix freely:
export SESSION_RECALL_EMBED_PROVIDER=openai-compatible
export SESSION_RECALL_EMBED_BASE_URL=https://embeddings.internal/v1
export SESSION_RECALL_EMBED_MODEL=your-model
export SESSION_RECALL_EMBED_DIM=1024A different embedder needs its own index. Vector tables are fixed-width, so changing
the model or dimension means rebuilding: delete ~/.local/share/session-recall/index.db
and re-run index. Session Recall fingerprints the embedding space of every indexed file
and refuses to mix spaces — semantic search shuts off with an explicit message instead of
returning misleading rankings.
nomic-embed-text is the local default because it is Apache-2.0 and installs in one
command. Stronger small models exist — jina-embeddings-v5-text-nano scores far higher for
its size — but they are CC BY-NC, which anyone indexing work history would be violating
without ever being told. If your use is genuinely non-commercial, point the variables above
at one. If you work in more than English, qwen3-embedding:0.6b (Apache-2.0) handles
multilingual history far better than nomic.
Keeping the index fresh
If you installed a plugin, this is already handled: the bundled SessionStart hook runs
session-recall index in the background on every session start, and incremental indexing
keeps it cheap.
In ~/.claude/settings.json:
"hooks": {
"SessionStart": [
{ "hooks": [ {
"type": "command",
"command": "sr=/abs/path/.venv/bin/session-recall; pgrep -f \"$sr index\" >/dev/null 2>&1 || (VOYAGE_API_KEY=... \"$sr\" index >/tmp/sr-index.log 2>&1 &)"
} ] }
]
}The pgrep guard prevents overlapping runs; ( … & ) detaches so session start doesn't
wait. Keep the host-level hook synchronous — the shell already backgrounds the indexer, and
Codex ignores Claude's async extension. A launchd/cron timer works too.
Team mode — ask a colleague's history
The same recall, across machines: pair with a colleague once, and your agent can ask their agent about their past work.
you → a colleague's agent: when you hit the local-launch problem with X — how did you solve it?
their agent (after the colleague approves the answer): pin the config to …, then …, and the problem does not come back.
What used to be a Slack thread and a half-remembered explanation becomes one question and one grounded answer. You never see the colleague's raw history — only the answer they approved.
Privacy here is mechanics, not policy:
questions and answers travel as end-to-end encrypted envelopes; the relay stores blind blobs it cannot read;
answers are built by an isolated read-only worker, scoped to the projects that contact was explicitly granted (
share allow);every candidate answer passes a secret scanner and then explicit owner approval (Telegram bot, or
share approvelocally) before it leaves the machine;a contact can be paused any time (
share pause), a peer revoked (share revoke).
Searching a peer's index needs no embedding setup on your side: the query travels as text, and the owner's worker embeds it with their own provider against their own index.
A fresh install has no transport and never talks to a server you didn't choose. The relay is blind — everything it carries is sealed and signed on the clients — so which one to use is coordination between peers, not a matter of trust.
Shared folder — zero infrastructure. Two accounts on one machine, or any folder both peers sync (Syncthing, Dropbox, an NFS mount):
export SESSION_RECALL_SHARE_TRANSPORT_DIR=~/Sync/sr-share # both peers, same folderYour relay on the LAN. One machine runs it, everyone points at it. Envelopes are end-to-end encrypted regardless, but this is plain HTTP — keep it to a network you trust:
session-recall share relay --port 8787 --host 0.0.0.0 # on the relay machine
export SESSION_RECALL_RELAY_URL=http://192.168.1.20:8787 # on every peerYour relay on the internet. The relay binds localhost on purpose and expects a TLS terminator in front (Caddy is the two-line option):
session-recall share relay --port 8787 # binds 127.0.0.1relay.example.com {
reverse_proxy 127.0.0.1:8787
}Then on every peer: export SESSION_RECALL_RELAY_URL=https://relay.example.com. The relay
stores only sealed blobs, and a mailbox is emptied on fetch. SESSION_RECALL_RELAY_URL=none
keeps an install network-silent on purpose. Put the export in your shell profile so agents
and timers see it too.
Pairing is a one-time ceremony with a short SAS check, then asking is one command:
session-recall share init # once per device, both sides
session-recall share invite # you: prints a one-time code
session-recall share join <code> # colleague: accepts it
session-recall share complete # you: finish the handshake
session-recall share trust <name> # both: confirm the SAS matched, name the peer
session-recall share allow <name> <project>
session-recall share notify # owner side: worker + approval loop
session-recall share ask <name> "how did you fix the local X launch?"
session-recall share fetch # collect the answersMeta docs — the project's memory, written down
Raw recall answers what was said. Meta docs answers what agents actually ask mid-task: was this bug fixed before? how do I perform this action? why was it decided this way? A daily job hands each session's dialogue — user messages and final answers, never the tool noise — to a distiller agent that maintains Markdown entries in a Git repository you choose:
<project>/bugs/— bugs that were actually fixed: how each was recognized, diagnosed, fixed, and proven fixed;<project>/actions/— procedures, step by step, written so an agent asked again can follow the entry alone;<project>/decisions/— contested choices: what was decided, why that way, what was rejected;USER/— a global map of where your information lives and how to find it (lookup commands and storage locations — never the stored values themselves).
session-recall metadocs init ~/meta-docs --from-today # memory starts now
session-recall metadocs run # one pass now
session-recall metadocs enable # daily job: launchd (macOS) / systemd user timer (Linux)
session-recall metadocs status
session-recall metadocs index-history --days 30 # opt-in: distill the past, onceThe distiller's whole world is four MCP verbs — search / create / edit / delete — and the
load-bearing rules are server mechanics, not prompt requests: create is refused until the
agent has searched (dedup is mandatory), entries are scanned for secrets before a byte
reaches disk, and delete demands a reason. Runs are incremental, and each changed project
gets its own local commit — review is a diff, undo is a revert, and sharing the memory with
a team is just pushing the repo somewhere private. Nothing is pushed unless you opt into
--push; the engine and model come from config only
(init --engine claude-cli|codex --model …) — nothing is picked silently.
Privacy is a hard invariant
This is a public repository. Only code goes in it. Runtime data lives under
~/.local/share/session-recall/, outside the repo tree — it physically cannot be committed.
Stays on your machine | Leaves only when you choose it |
Original Claude Code and Codex transcripts | Conversation surface text → your configured hosted embedder |
Cursor's SQLite store and its normalized snapshots | An explicitly approved team-mode answer |
Tool calls, outputs, reasoning — the whole raw trace | Nothing, on the bundled/local embedding path |
The SQLite index and stored vectors |
API keys are environment variables only;
.gitignoreblocks.env.Tests use synthetic fixtures, never a real slice of a session.
The bundled provider keeps the entire indexing path on-device. If you choose a hosted provider, pick one you trust with your transcript surface text.
Troubleshooting
Start here — it checks the whole chain and exits non-zero when something is actually broken, so it also works from a timer:
$ session-recall health
[ok ] Freshness 2 minutes behind
[warn] Embedder responded in 5828 ms
→ slow provider will make indexing crawl
[ok ] Vector space builtin/BAAI/bge-small-en-v1.5/384
[ok ] Corpus 1054 sessions (claude 373, codex 680, cursor 1)
[ok ] Sources claude, codex, cursor present
verdict: AMBER (voyage/voyage-4-large, index at ~/.local/share/session-recall/index.db)Freshness compares the newest transcript on disk against the newest turn in the index, so an indexer that runs on every session and fails every time still shows as behind — exactly the failure that is otherwise invisible.
Symptom | Cause / next step |
| The embedding provider is unreachable — only literal matching ran. Results are real, but a miss proves nothing. |
| The index was built in a different embedding space. Run |
Indexer logs | Not your key: a WAF is blocking your IP (common on VPN and datacenter exits). The same 403 appears with no key at all. Route egress elsewhere or switch provider. |
| A SOCKS proxy is set in the environment but |
| The indexer has not succeeded recently. Run |
Cursor lives in a custom profile | Set |
Development
git clone https://github.com/AbsoluteMode/session-recall.git
cd session-recall
python -m venv .venv
.venv/bin/pip install -e ".[dev]"
.venv/bin/pytest -qTo register the MCP server by hand instead of using the plugin:
claude mcp add session-recall --scope user -- /absolute/path/.venv/bin/session-recall-mcpEngineering rationale and invariants live in docs/decisions/. Start with:
Roadmap
Hosted/team index — one shared index for a team instead of per-machine copies. The honest open question: whoever searches must embed the query, so a shared vector space implies a shared embedding path.
Per-contact approval bypass — skip per-answer approval for peers you fully trust; today every answer is approved explicitly.
More histories — other agents' transcripts beyond Claude Code, Codex, and Cursor.
Contributing
Issues, documentation improvements, host adapters, and translations are welcome. Keep fixtures synthetic and never commit real transcripts, indexes, embeddings, or credentials.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseAqualityDmaintenanceSemantic search across Claude Code conversations. Hybrid vector + keyword search, fully local, background indexing.61037MIT
- Alicense-qualityCmaintenanceEnables searching and retrieving Claude Code conversation history via hybrid semantic and keyword search, allowing the agent to access its own past interactions.4MIT
- Alicense-qualityDmaintenanceLocal memory search for Codex and Claude Code conversations. It keeps history on your machine, builds a local graph index, and returns compact evidence from past sessions.5MIT
- AlicenseAqualityAmaintenanceProvides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.55MIT
Related MCP Connectors
Persistent memory for AI agents. Search, store, and recall across sessions.
Long-term memory for AI assistants. Hybrid retrieval, query expansion, auto-topics.
Persistent memory for AI agents — verbatim conversations, searchable by meaning.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/AbsoluteMode/session-recall'
If you have feedback or need assistance with the MCP directory API, please join our Discord server