Havuz

One zero-dependency MCP gateway CLI for every server and agent skill. Token optimization, tool discovery and context compression: 71,929 ->

CDAF (Cached Descriptive Asset Files) - open sidecar format for video so AI agents stop re-analyzing the same footage. Spec, CLI, agent skil

An effective and efficient coding-agent setup in under 30 seconds: best tools, unified instructions, any OS.

Menu bar app for macOS, Windows and Linux that cuts Claude Code and ChatGPT Codex token costs by ~50%

Open-source, local-first AI coding agent usage and cost dashboard for Claude Code, Codex, Cursor, OpenCode, Kiro, and Pi.

Honey (I Shrunk the AI) by GreenPT: a cross-tool coding skill that cuts AI coding-agent token usage and LLM API costs — write less code, les

Portable project memory across Claude Code, Codex and OpenCode, plus token accounting measured from harness transcripts. Local file I/O, no

Local proxy that compresses your LLM API requests so you pay less, with no change to the answers. Trims wasted tokens from prompts, history,

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts

Claude Code plugin that tracks token usage, identifies wasted context, and saves 30-50% on API costs. Heatmaps, ROI reports, budget alerts,

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — with its own 7-tool agent loop, workspace-scoped file access, and bounded

Tura, coding agent’ların birden çok araç adımını tek bir runtime-managed command graph içinde çalıştırarak tekrar eden LLM çağrılarını azaltmayı hedefleyen açık kaynak bir agent runtime harness’tir.

Neden yükseliyor · 83 günde 644 yıldız ve son 28 günde 18 commit dikkat çekiyor; token tasarrufu vaadini karşılaştırmalı benchmark’larla desteklemesi de ilgiyi artırmış olabilir. Ancak son 28 gündeki 2 farklı yazar, katkı tabanının hâlâ sınırlı olduğuna işaret ediyor.

Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt

Auto AI improver. Cost and token burn reducer, turn saver, and focus keeper for Claude Code, Codex, Copilot, Gemini, and more: surgical read

Put everything on your wallpaper. Terse is a live 3D particle wallpaper for macOS & Windows: synced song lyrics, notifications, window title

lowfat - slim your command output. strips noise, saves tokens.

The one place for the skills, keys and memory of every agent you use. Formerly OMNI.

Independent research on Claude Code internals, Claude Agent SDK, and related tooling.

One command gives AI agents instant codebase context. ~250 tokens replaces 50,000+ tokens of exploration. Auto-configures Claude Code, Curso

ctx-wire runs your commands, compresses the output with declarative filters, scrubs secrets, and hands your agent a short result. The full l

Local-first flight recorder for coding agents : replay every run as a live session map, score the context bill, and write the fix back into

EGC gives every AI coding agent the same brain. Shared memory, skills, and live context across Cursor, Claude Code, Copilot, Aider, and 29 A

The AI-native wire format for structured data. 100% comprehension on every frontier model. 50-92% fewer tokens than JSON. 43B+ lossless roun

Agentic Runtime

Cut Claude Code costs with sourced levers -- prompt caching, model routing, Batch -- plus an installable skill, CLI tools, a cost calculator

LLM-ready reasoning surface over logs

Fast, AI-agent-native code search in Rust — hybrid BM25 + semantic, Tree-sitter AST chunking, dependency & impact analysis. Drop-in replacem

CTX - Context Runtime Engine for Coding Agents

State aware knowledge compression, ingestion, and hybrid retrieval engine. Zero dependencies. Sub-100ms queries.

Cut context bloat in your AI-agent stack: find and safely prune unused skills, MCP servers and subagents from real transcript evidence

Measured, monotonic, lossless input savings for Codex.

Quieter sessions for Claude Code: less narration, shorter tool output and concise answers focused on the result.

Eco mode for Claude Code. /eco: -31% to -73% output tokens with critical findings intact; /eco-max: up to -75% with lowered effort. Measured

token-ninja routes deterministic shell commands locally — zero LLM calls, ~19µs latency. Works silently inside AI tools via MCP.

MCP server for Unity Editor — 160 tools for scene, assets, animation, VFX, playtest & more

A lossless token-optimization codec for LLM agents — cut input tokens up to 82%, nothing dropped, every fact kept. Drop-in proxy + one-line

Stop Claude Code from burning through your quota in 20 minutes. Auto-rotates oversized sessions and preserves context.

Generate a compact codebase index for AI assistants — saves 50K+ tokens per conversation

The context spine that 10x's every AI coding session. Live in 8 IDEs (Claude Code, Cursor, Cline, Continue, Aider, Codex, Windsurf, Zed) via

A drop-in proxy that compresses bloated code context in real-time, cutting LLM API costs by 50–80% without losing what the model actually ne

Turn Google Drive PDFs into Obsidian wiki notes via NotebookLM MCP without loading full PDFs into Claude context

Token-efficient MCP server for tabular data retrieval. Index CSV/Excel files, query rows, aggregate — 99%+ token savings vs raw file reads.

Zed extension for Headroom — context compression for AI agents

Carves your agent's tool outputs down to what matters. Never cuts what doesn't come back.

Claude Code skills for developers who code like cats — never more effort than the problem requires.

CLI output compressor for Claude Code. Reduces token consumption by 50–90% by compressing verbose command output before it enters the con

Token-budget-aware graph navigation for AI coding agents. Serve exactly the noodles your LLM needs. 🍜

Keep Claude Code context clean. Open-source toolkit: drift detection, re-read dedup, integrity scoring, AST-aware reads, 15 MCP tools. 62.6%

Audit and shrink your Claude Code startup context. Measures what every skill, plugin, agent, and memory file costs in the system prompt, the

MCP-native code retrieval for AI agents — 84-88% fewer read tokens, BM25F + semantic search, AST chunks, session dedup