Tokenadevstoken-savior

Best alternative to token-savior

Tokenade is the best alternative to token-savior — Universal token-optimization engine for AI coding agents — native hooks for 18 agents combine output filtering, semantic code search, skeleton compression, sandboxed execution, MCP proxying and a live savings dashboard in a single dependency-free binary.

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Tokenadetoken-savior

Output Filtering

Format-aware compactors cover git, cargo, kubectl, terraform, docker and more — 60–99% reduction on the noisiest commands. Command rewriting further trims source-side before the shell even runs.

Output Filtering

34 Bash compactors covering git, gh, pytest, jest, kubectl, aws, docker, npm/pip, grep/find/cat/curl — plus a PreToolUse Bash rewriter with 10 safe densification rules. 7-day bench: ~20.4k tokens/week saved at 68.9% mean compaction.

Semantic Code Search

Finds the most relevant files for a task and sends only those to the model, instead of the whole repo. Runs fully on-device with no external vector database and no model downloads — fast even on large codebases.

Structural Code Search

tree-sitter structural indexing (10+ languages) with find_symbol, get_function_source, search_codebase, detect_breaking_changes and find_dead_code. No dense vector search — keyword and AST traversal only.

Skeleton Compression

Signatures-only view of source files, YAML, Markdown and Terraform — −64% on file reads while preserving every top-level declaration. Stacks on top of output filtering for maximum savings.

Persistent Memory & Manifest Reduction

Persistent memory engine with Bayesian validity + ROI ranking; tiny_plus profile reduces MCP manifest to ~1.5k tokens vs lean's ~4k. No skeleton/signatures-only file compression.

Third-Party MCP Optimization

tokenade mcp-proxy wraps any third-party MCP server's launch command in the agent's MCP config, so every tool result (verbose JSON, logs, console output) is folded on the way back — set once, not per call. Image results pass through untouched.

MCP Tool Profiles

4 tool profiles (optimized=15 tools, tiny=6, lean=51, full=68) let the user control manifest cost. No adaptive filtering based on installed binaries.

Mechanism Breadth

The only tool combining output filtering + semantic search + skeleton compression + sandbox execution + MCP proxying + secret redaction + content-addressed cache in a single binary. On the open THOL benchmark (Claude Code 2.1.183 campaign) it is the only tool measured significantly cheaper than the control: cost ratio 0.84 [0.72, 0.95], 120/120 successful runs.

Mechanism Breadth

Bash compactors + tree-sitter code nav + persistent memory + vector embeddings + manifest profiles. The most multi-layered Python MCP server in this comparison; narrower than tokenade's full stack.

Savings Dashboard

tokenade dashboard shows measured savings, per-command and per-project breakdown, and framework-detection status. Local logs rotate automatically with built-in secret redaction.

Savings Analytics

ts_discover MCP tool scans session transcripts for missed optimization opportunities. No live dashboard; analytics are retrospective.

token-savior at a glance

token-savior starts at Free (open source). Python MCP server combining tree-sitter structural code navigation (10+ languages), 34 Bash output compactors, a persistent memory engine with vector embeddings, and PreToolUse Bash rewriting — reporting 97.9% accuracy at −80% tokens on tsbench.

Pros

  • Highest published benchmark: 97.9% accuracy at −80% tokens on tsbench (96 real tasks, Claude Opus 4.7)
  • 34 Bash compactors covering git, gh, pytest, jest, kubectl, aws, docker, npm/pip, grep/find/cat/curl
  • Persistent memory with Bayesian validity + ROI ranking across sessions
  • Tiny/plus profile (~1.5k tokens) vs lean (~4k tokens) for manifest cost control
  • 1688 passed tests + CI on Python 3.11/3.12/3.13 — well-tested for its size

Cons

  • Python runtime: slower cold startup compared to compiled Rust or Go tools
  • Primarily targets Claude Code; limited support for other agents
  • Memory engine requires opt-in TS_AUTO_EXTRACT flag and an LLM API key for extraction
  • Bash compactors tuned to 34 specific patterns; extending for custom commands requires fork

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