A per-project semantic search tool that indexes Claude Code session transcripts into SQLite and retrieves relevant past context via embeddings or full-text search. Designed for individual developers to quickly find decisions and discussions across session history without centralizing data.
Per-project semantic search over Claude Code session history. Indexes JSONL transcripts into SQLite; retrieves via bge-m3 embeddings (Ollama) with FTS5 fallback.
README
session-indexer
Per-project semantic search over Claude Code session history. Indexes JSONL transcripts into a per-project SQLite store; retrieves via bge-m3 embeddings (Ollama) with FTS5 BM25 fallback. Automatically injects relevant past context at session start.
Problem it solves: returning to a project after a week and needing to find
"what did we decide about X" across dozens of past sessions. session-end
gives you "where I left off last time"; session-indexer gives you "what we
discussed across all history" — by semantic similarity, not grep.
Scope: single developer, single machine. This indexes your own individual sessions with Claude Code in a project — not a team's shared history, not a multi-user store. If you need to share findings with teammates, that's a conversation/PR/doc, not something this tool does. See below for why that's a deliberate choice, not a limitation.
Why not a centralised memory tool?
mempalace,
agentmemory, and
MemMachine all run on a single
shared backend — mempalace in ChromaDB, agentmemory via an iii engine MCP
server, MemMachine via a Neo4j + SQL backend behind a REST server
(self-hosted or their managed cloud; MemMachine does add logical per-tenant
isolation via org/project IDs, unlike the other two). That single-backend
architecture still has one fatal flaw: if it dies, everything on it dies
at once. A corrupt ChromaDB index, a crashed MCP server, or an unreachable
MemMachine/Neo4j instance takes down memory for every project and tenant
depending on that instance simultaneously, and recovery is non-trivial.
MemMachine in particular targets multi-tenant SaaS agent products (CRM,
healthcare, finance assistants) — a different problem than a solo dev's
per-project recall tool.
session-indexer is per-project and append-only (.claude/sessions.db lives
inside the project's .claude/ dir). The worst failure mode is losing one
project's DB — fully recoverable by re-running mine on the available JSONLs,
since mine is idempotent. Every project is isolated; nothing you do in one
can break another.
Prerequisites
- Go 1.26.5+ — to build the binary
- Ollama — for vector embeddings (optional but recommended)
- Install: ollama.com/download — native packages for macOS, Linux, Windows
ollama pull bge-m3:latest— 1024-dim multilingual model (EN + UA)
- jq — used by hooks and
/recallfor JSON formatting
Quick Start
# 1. Build and install the binary
go install ./cmd/session-indexer
# 2. (Optional) Pull the embedding model
ollama pull bge-m3:latest
# 3. Wire the hooks into your project (one-time setup)
# Copy session-index.sh + session-recall.sh → .claude/hooks/
# Update .claude/settings.local.json with Stop + SessionStart entries
# /recall is a user-level skill (~/.claude/skills/session-recall/, symlinked
# from ~/wrk/common/skills/session-recall/) — no per-project install needed.
# See "Hook Setup" below for the exact steps.
# 4. End a Claude Code session — Stop hook mines it into .claude/sessions.db
# (The hook silently no-ops until session-indexer is in PATH)
# 5. Open a new session — SessionStart hook injects relevant past context
# automatically based on current git branch + recent commits
# 6. Search manually at any time
session-indexer search "config validation approach" --db .claude/sessions.db
# or from inside Claude Code:
# /recall config validation approach
Build
go build -o bin/session-indexer ./cmd/session-indexer
go install ./cmd/session-indexer # to PATH (activates the Stop hook guard)
Usage
session-indexer mine <jsonl-path> --db .claude/sessions.db
session-indexer search <query> --db .claude/sessions.db [--limit N] [--json]
session-indexer embed --db .claude/sessions.db
session-indexer stats --db .claude/sessions.db
session-indexer distill --db .claude/sessions.db [--threshold 0.7] [--model <name>]
session-indexer facts search <query> --db .claude/sessions.db [--limit N] [--json] [--include-expired]
session-indexer facts get <id> --db .claude/sessions.db [--json]
session-indexer facts related <id> --db .claude/sessions.db [--json]
session-indexer facts supersede <new-id> <old-id> --db .claude/sessions.db
mine output
mined: 23 chunks inserted, 21 embedded, 0 skipped, 2 deferred
- inserted — new chunks stored (duplicates skipped via INSERT OR IGNORE)
- embedded — chunks that got a vector embedding from Ollama
- skipped — embed errors (Ollama returned an error); stored in DB, no embedding, backfill via
embed - deferred — embed deadline hit (50s ctx timeout); stored in DB, no embedding, same backfill path
search --json output schema
[
{
"SessionDate": "2026-06-10",
"Role": "user",
"Content": "We decided to use a ring buffer for the event queue…",
"Score": 0.847
}
]
Score is cosine similarity (0–1) in embedding mode, or negated BM25 rank in
FTS5 fallback mode (higher is always better in both cases).
Facts layer — distill and facts
A separate, manually-invoked layer that distills durable
subject-predicate-object facts from mined chunks via an LLM call, alongside
the raw-text search above. Never runs automatically — not wired into the
Stop hook, no deadline. See "Facts Layer"
in the architecture doc for the full design (confidence gate, supersession
safeguards).
# Extract facts from chunks not yet distilled (idempotent — safe to re-run)
session-indexer distill --db .claude/sessions.db --threshold 0.7
# → Distilled 12 chunks: 5 facts stored, 3 below threshold, 1 superseded
# Query
session-indexer facts search "implementation status" --db .claude/sessions.db
# → [7] session-indexer | has | 33 merged PRs (confidence 0.92)
session-indexer facts get 7 --db .claude/sessions.db
# → shows the fact plus any incoming/outgoing supersedes edges
session-indexer facts related 7 --db .claude/sessions.db
# Manual override (audit/backstop — distill already judges supersession automatically)
session-indexer facts supersede 9 7 --db .claude/sessions.db
Embeddings
Requires Ollama on localhost:11434 with bge-m3:latest. Override with
environment variables:
| Variable | Default | Description |
|---|---|---|
OLLAMA_HOST |
http://localhost:11434 |
Ollama base URL (scheme optional: localhost:11434 works) |
OLLAMA_MODEL |
bge-m3:latest |
Embedding model name |
OLLAMA_DISTILL_MODEL |
glm-5.2:cloud |
Chat/generate model used by distill — distinct from OLLAMA_MODEL, must be pulled separately (ollama pull glm-5.2:cloud or your chosen model). Override per-invocation with distill --model <name> (wins over the env var). |
mine runs with a 50s context.Context deadline (headroom under the 60s
Stop-hook budget): storing is fast and unconditional; embedding respects the
deadline. Chunks past the deadline are stored but Deferred (no embedding row);
backfill with session-indexer embed. Embed errors count as Skipped — same
storage state, same backfill path, different cause.
When Ollama is unavailable or the store has zero embeddings, search falls back
to FTS5 BM25 with per-term OR recall and notes this in the output.
Hook Setup
Two Stop hooks run on every session end (wired in a single Stop entry of
settings.local.json — Claude Code 2.1.x runs only the first top-level entry):
{
"hooks": {
"Stop": [
{
"hooks": [
{ "type": "command", "command": "bash .claude/hooks/session-end.sh", "timeout": 60 },
{ "type": "command", "command": "bash .claude/hooks/session-index.sh", "timeout": 60 }
]
}
],
"SessionStart": [
{
"hooks": [
{ "type": "command", "command": "bash .claude/hooks/session-last.sh", "timeout": 10 },
{ "type": "command", "command": "bash .claude/hooks/session-recall.sh", "timeout": 15 }
]
}
]
}
}
session-index.sh silently no-ops until session-indexer is on PATH.
session-recall.sh no-ops until .claude/sessions.db exists (after the first indexed session).
Hook logs go to ~/.cache/<project-name>/hooks.log.
FAQ
Why isn't .claude/sessions.db committed to the repo? Won't I lose it?
.claude/sessions.db is gitignored on purpose. Two independent reasons come
up when people ask this, and it's worth separating them:
- "Should the whole team see this DB?" — No.
session-indexerindexes your own individual sessions with Claude Code, not a team-shared history (see "Scope" above). Committing it to the project repo would put one person's session log in front of every collaborator on every PR, for no benefit — nobody else's Claude Code instance reads or needs it. Adding it to git also means merge conflicts on every commit touching the DB, since SQLite files aren't line-mergeable. - "But what if I lose the machine / disk?" — That's a real, separate
concern: backup, not team sharing. The DB is fully rebuildable from your
local JSONL transcripts (
session-indexer mineis idempotent — see UC-8 indocs/use-cases.md), so the worst case is re-mining, not permanent loss, as long as the transcripts themselves survive. If you want the DB backed up beyond that, the right place is your own personal dotfiles/backup tooling (e.g. a private dotfiles repo, Time Machine, restic) — not the project repo, since that would reintroduce the team-visibility and merge-conflict problems above for a file only you need. Whether to back it up at all is entirely your call; the tool takes no position on it beyond keeping it out of the shared repo.
What about git worktrees — does each worktree get its own DB?
Currently, yes: .claude/sessions.db resolves relative to whichever
checkout Claude Code is running from, and Claude Code uses linked git
worktrees by default for isolated work. Since .claude/sessions.db is
gitignored, a linked worktree doesn't see the main checkout's existing DB
and starts indexing independently, splitting your session history across
worktrees rather than sharing it. This is a known limitation, not
intentional design (per-project isolation is intentional — see
docs/requirements.md FR-3 — worktree splitting
within one project isn't). If this affects your workflow, open an issue.
Querying facts (discipline)
The facts layer is a supersedable claim store, not a flat lookup table — a
matching search hit is not automatically the current truth. For any
non-trivial answer drawn from facts, follow all four steps before citing
a fact:
facts search <query>— find candidate facts.facts get <id>— read the fact plus its supersedes edges.facts related <id>— check for an incoming supersedes edge (a newer fact that replaced this one). If present, jump to the newer fact and repeat from step 2.- Check
until— a non-nulluntilmeans the fact is tombstoned; don't cite it as current (it's still visible via--include-expiredfor historical context, but never as present-tense truth).
Anti-pattern: answering after step 1 alone. facts search ranks by
keyword match, not recency or validity — a stale, superseded fact can
easily outrank its replacement on pure BM25 score if it happens to phrase
the query terms more directly. Skipping steps 2–4 is exactly how a
distilled-but-superseded fact (e.g. an old "implementation not started"
claim) gets cited as current truth — the same class of drift this feature
exists to catch.
Troubleshooting
Hooks not running:
Check that both commands are in the same Stop entry's hooks array (not two
separate top-level Stop entries). See Hook Setup above.
Schema version mismatch:
schema version mismatch (X != Y): delete .claude/sessions.db and re-mine to rebuild
Delete the DB and re-run mine on your JSONLs — mine is idempotent.
Search returns poor results / FTS5 fallback:
session-indexer stats --db .claude/sessions.db # check pending count
session-indexer embed --db .claude/sessions.db # backfill embeddings
Search warns "N chunks not yet embedded — results may be incomplete":
Some chunks are stored but have no embedding (interrupted mine, Ollama was
down, or deadline hit). Cosine search only ranks embedded chunks — unembedded
ones are invisible until backfilled. FTS5 fallback only activates when zero
embeddings exist, not for a partial store. Fix: run session-indexer embed.
Read hook logs:
tail -40 ~/.cache/$(basename "$(git rev-parse --show-toplevel)")/hooks.log
DB size: scale assumption is <10k chunks (~40MB vectors in memory). No hard
limit, but search loads all embedding rows into memory for cosine; if the DB
grows beyond ~50k chunks, revisit.
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