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token-savior

GitHub
Website

The MCP server that turns Claude into the only coding agent hitting 100% on a real benchmark. -77% active tokens, -76% wall time, 0 losses across 96 tasks on Claude Opus 4.7. Structural code navigation + persistent memory. Works with every MCP client.

1,021
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<!-- mcp-name: io.github.Mibayy/token-savior-recall --> <div align="center">

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.

Version
PyPI
Tests
Benchmark
Python 3.11+
MCP
CI

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)

Plain Claude CodeWith Token Savior
Score141 / 180 (78.3%)188 / 192 (97.9%)
Active tokens / task17 2213 395 (-80%)
Wall time / task110.6 s18.9 s (-83%)

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

</div>

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)

FamilyCompactors
gitstatus, diff, log, push/pull, commit, add, fetch, checkout, branch, worktree list, stash list
ghrun list, run view, pr diff, pr view, issue view, repo view
test/lintpytest, jest, vitest, eslint, biome, cargo test, cargo build/clippy, tsc
cloudkubectl get, kubectl logs, aws sts, aws ec2, aws lambda, aws logs, aws iam, aws dynamodb, aws s3
dockerdocker ps, docker logs
packagingnpm/yarn/pnpm list, pip list/show
shell catch-allsgrep, find, cat, curl

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

ProfileTools exposedManifest tokensWhen to use
optimized15~1.5 KTRecommended default -- Pareto win on tsbench
autoadaptive~1-2 KTPer-client telemetry-based (experimental)
tiny6~0.6 KTMinimal hot loop
lean51~4 KTLegacy -- broader surface
full68~6 KTEverything exposed

You probably want optimized.


Token savings

OperationPlain ClaudeToken SaviorReduction
find_symbol("send_message")41M chars (full read)67 chars-99.9%
get_function_source("compile")grep + cat chain4.5K charsdirect
get_change_impact("LLMClient")impossible16K charsnew capability
96-task tsbench (Opus, plain vs ts)17 221 active/task3 395 active/task-80%
7-day Bash output bench (v4.3)~30 K tokens/week~9.6 K tokens/week~20.4 K/week

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

VarPurpose
TS_BASH_COMPACT=1Enable PostToolUse Bash output compactors
TS_BASH_REWRITE=1Enable PreToolUse Bash command rewriter
TS_BASH_REWRITE_LOGJSONL audit log of every rewrite
TS_COMPACT_INLINE_THRESHOLDHybrid mode threshold (default 4 KB)
TS_COMPACT_TINY_THRESHOLDSkip-sandbox threshold (default 256 B)
TELEGRAM_BOT_TOKEN + TELEGRAM_CHAT_IDCritical-observation feed
TS_VIEWER_PORTWeb viewer dashboard
TS_AUTO_EXTRACT=1 + TS_API_KEYLLM auto-extraction of memory observations
TS_CAPTURE_DISABLED=1Skip read-side capture sandboxing (default in optimized)
TS_MEMORY_DISABLE=1Silence memory hooks (clean-context workloads)

License

MIT

Repository

MI
Mibayy

Mibayy/token-savior

Created

March 30, 2026

Updated

June 15, 2026

Language

Python

Category

AI