Token Savior -- v4.3

One MCP server. One profile. 97.9% on tsbench at -80% tokens. Structural code navigation, persistent memory, and Bash output compaction for AI coding agents.

mibayy.github.io/token-savior -- project site + benchmark landing github.com/Mibayy/tsbench -- benchmark source + fixtures

Benchmark -- 96 real coding tasks (Claude Opus 4.7, May 2026)

Reproduces with the optimized profile (single env var). See BENCHMARK-SUMMARY.

What's new

v4.3.0 -- bench-driven coverage push (May 2026)

Real-world bench against 7 days of transcripts (1130 Bash outputs) drove this release. Cumulative savings now sit at ~20.4 K tokens/week (19.3% match rate, 68.9% mean compaction) vs ~12 K/week on v4.2.0.

• Fixed pytest regex: now matches python3 -m pytest, uv run pytest, venv-prefixed forms, poetry/hatch/pdm/rye run pytest.
• 5 more git compactors: fetch, checkout, branch, worktree list, stash list.
• 4 more gh compactors: gh repo view, gh pr view, gh issue view, gh pr diff.
• grep, find, cat compactors. Group hits by file, strip common prefix, head/tail truncation. 83-96% savings on the fixtures.
• Compound command splitter: cd /root/foo && git status now compacts by picking the last meaningful segment of &&/; chains. Bails on subshells, heredocs, pipes, loops, unterminated quotes.

v4.2.0 -- coverage + hybrid mode + ts init

• 12 more compactors: jest, vitest, eslint, biome, kubectl get/logs, aws sts/ec2/lambda/logs/iam/dynamodb/s3, npm/yarn/pnpm list, pip list/show, curl. Peaks: 91.7% on aws ec2, 95% on jest all-green.
• Hybrid sandbox+compact mode. When a compactor matches but the compact text is still bulky (> 4 KB), the hook emits the compact preview AND sandboxes the full original. The agent can pull it via capture_get if it needs the detail.
• ts init --agent {claude,cursor,gemini,codex} CLI. Detects agent settings, deep-merges the hook config, dedups by (matcher, command), prints a unified diff, backs up settings.json, idempotent on re-run.
• ts_discover cross-project + format="adoption" reports TS-vs-native ratios per session with first/second-half trend.

v4.1.0 -- RTK-inspired Bash compaction + discover

• 14 Bash output compactors in a PostToolUse hook: git status/diff/log/ push/commit/add, pytest, cargo test/build/clippy, tsc, docker ps/logs, gh run list/view. Median 63%, peak 100% (a green pytest -q collapses to one line).
• PreToolUse Bash rewriter. Bare commands get denser variants before execution: git status -> --porcelain=v2 --branch, tsc -> --pretty false, pytest -> -q --tb=line, etc. 10 safe rules, guarded against composition operators and explicit verbose flags.
• get_usage_stats v2. ASCII sparkline (30 d), daily breakdown table (7 d), top-tools cumulative, format="json".
• New MCP tool ts_discover. Scans ~/.claude/projects/*/*.jsonl transcripts and flags missed TS opportunities (Read->Grep->Read chains, sequential find_symbol, edits without get_edit_context, memory_search without prior memory_index, native shell on code files). 30-day scan in ~2.5 s on a 343 MB transcript dir.

Quick start

pip install "token-savior-recall[mcp]"

Add to your MCP config (e.g. Claude Code):

{
  "mcpServers": {
    "token-savior-recall": {
      "command": "/path/to/venv/bin/token-savior",
      "env": {
        "WORKSPACE_ROOTS": "/path/to/project1,/path/to/project2",
        "TOKEN_SAVIOR_CLIENT": "claude-code",
        "TOKEN_SAVIOR_PROFILE": "optimized"
      }
    }
  }
}

That's it. TOKEN_SAVIOR_PROFILE=optimized ships the Pareto-optimum config that wins tsbench. It bundles:

• tiny_plus (15 hot tools manifest)
• thin inputSchema (-44% manifest)
• capture sandbox disabled
• memory hooks gated for cross-project safety

No other tuning needed.

Activation (Bash compaction + rewriting)

Bash compaction and the PreToolUse rewriter are opt-in. Two env vars and one CLI call:

export TS_BASH_COMPACT=1       # PostToolUse output compactors (34 of them)
export TS_BASH_REWRITE=1       # PreToolUse command rewriter (10 rules)

ts init --agent claude --yes   # auto-merge hooks into ~/.claude/settings.json

ts init is idempotent. It detects existing hook entries, dedups by (matcher, command), prints a unified diff, and backs up settings.json to .bak-YYYYMMDD-HHMMSS (UTC) before writing. Supported agents: claude, cursor, gemini, codex. Pass --dry-run to preview, or --global to write the user-level config.

Optional audit log of every rewrite:

export TS_BASH_REWRITE_LOG=$HOME/.local/state/token-savior/rewrites.jsonl

Compactor catalog (34)

Each compactor is a pure function (no I/O, no globals) returning a token-efficient rendering. The dispatcher returns None when no matcher fires, leaving the existing sandbox path untouched. Compound commands (cd ... && cmd) fall through to the last meaningful segment.

ts_discover -- find missed TS opportunities

New MCP tool that scans your Claude Code transcripts for patterns where TS tools would have been cheaper than what the agent actually did.

ts_discover()                       # active project, last 30 days
ts_discover(project=None)           # ALL transcript projects
ts_discover(format="adoption")      # TS vs native ratio per session
ts_discover(format="adoption_json") # same, JSON

Findings: Read->Grep->Read chains, sequential find_symbol, edits without get_edit_context, memory_search without memory_index, native shell on code files. Args are pruned to load-bearing keys (PII-safe). Streams JSONL with mtime fast-skip.

ts init CLI

ts init --agent claude [--global] [--dry-run] [--yes]
ts init --agent cursor
ts init --agent gemini
ts init --agent codex

Detects the target agent's settings location, deep-merges the Token Savior hook config (PostToolUse + PreToolUse), preserves existing hooks, dedups, prints a unified diff. Backs up to settings.json.bak-YYYYMMDD-HHMMSS (UTC). Re-running is a no-op.

What it does

Claude Code reads whole files to answer questions about three lines, and forgets everything the moment a session ends. Token Savior fixes both, plus a third axis: it now compacts the noisy Bash output that bloats turn budgets between code reads.

It indexes your codebase by symbol -- functions, classes, imports, call graph -- so the model navigates by pointer instead of by cat. Measured reduction: 97% fewer chars injected across 170+ real sessions.

On top of that sits a persistent memory engine. Every decision, bugfix, convention, guardrail and session rollup is stored in SQLite WAL + FTS5

• vector embeddings, ranked by Bayesian validity and ROI, and re-injected as a compact delta at the start of the next session.

And on top of that, since v4.1, sit the Bash compactors and the PreToolUse rewriter. Bench numbers above.

Profile comparison

You probably want optimized.

Token savings

Install

pip (MCP server)

pip install "token-savior-recall[mcp]"
# Optional hybrid vector search:
pip install "token-savior-recall[mcp,memory-vector]"

uvx (no venv, no clone)

uvx token-savior-recall

Claude Code one-liner

claude mcp add token-savior -- /path/to/venv/bin/token-savior

Development

git clone https://github.com/Mibayy/token-savior
cd token-savior
python3 -m venv .venv
.venv/bin/pip install -e ".[mcp,dev]"
pytest tests/ -q

Suite size: 1688 passed, 55 skipped on main. CI green on Python 3.11 / 3.12 / 3.13.

Bench it yourself

The compactor numbers above come from replaying real Claude Code transcripts through the dispatcher. Two scripts live under scripts/:

python3 scripts/bench_compactors_real.py       # match rate + mean savings
python3 scripts/bench_compactors_unmatched.py  # top unmatched commands

The first walks ~/.claude/projects/*/*.jsonl, replays every Bash output through the registry, and reports per-family savings + overall match rate. The second buckets the unmatched commands so the next compactor target is obvious from the histogram.

To reproduce the tsbench score:

git clone https://github.com/Mibayy/tsbench && cd tsbench
python3 generate.py --seed 42
git tag v1
python3 breaking_changes.py
git tag v2
TS_PROFILE=tiny_plus TS_CAPTURE_DISABLED=1 python3 bench.py --tasks all --run B

Bonus: ts CLI for non-MCP agents

For agents without MCP (Cursor, Aider, Continue, scripts, CI), the ts command exposes a subset of the tools via shell:

ts use /path/to/project
ts get my_function          # JSON output
ts search 'pattern'
ts daemon start             # ~145ms per call vs 1.5s cold fork
ts init --agent cursor      # wire up Bash hooks for non-Claude agents

On Claude Code, prefer the MCP server -- measured cheaper than CLI on Opus 4.7. The CLI is there for the portability case.

Optional env vars

License

MIT