Measure token savings per AI coding agent, optimize context, and share a live local knowledge graph across 16 CLI clients.

🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman

Every file not opened. Every folder not explored. Tokens saved. ProjectAtlas guides coding agents with purpose metadata and an intelligent code graph, reducing token costs by over 90%.

Cut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.

CLI proxy that reduces LLM token consumption by 60-90% on common dev commands. Single Rust binary, zero dependencies

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

MCP server for Git with local Ollama — zero tokens for git operations

Hooks that force Claude Code to use LSP instead of Grep for code navigation. Saves ~80% tokens

Save 40%+ on agent token costs with code graphs: call graphs, dependency graphs, dead code detection, and blast radius analysis.

Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors

AI Badger - Local-first tool that extracts focused repo context for any AI chat (Claude, ChatGPT, Grok, etc.) without wasting tokens on irrelevant files.

External-agent-first orchestration for AI coding workflows: dispatch to Antigravity CLI, Grok CLI, Claude Code, and Codex CLI with structured receipts, recovery, and low-token wait/watch.

High-performance code-intelligence engine for AI agents and IDE, supports 257 languages, multi repositories, based on graph, with access via CLI, MCP Server, and API. AI coding agents teammate - expose only needed information, cutting token usage up to 50x. 100% local. Discord: https://discord.gg/39MFHu3J5d

A structured 3-agent AI dev team — Architect, Builder, Reviewer. Built from production use. Token-optimized. Works with Claude Code, VS Code, Cursor, and any AI that supports context files.

See what Claude Code and Codex actually send to the API — and what each part costs.

Multi-model orchestration subagents for Claude Code — delegates by task scope to Gemini's 1M-token context or GPT's fast iteration, then routes every result back through Claude review.

Framework-aware code intelligence MCP server for Claude Code and Codex — 70.5% fewer input tokens to review a pull request, median over 60 merged PRs in repos we don't own, comprehension at parity. 81 languages, 87 frameworks. Your code and index never leave the machine; an anonymous usage ping is on by default and opt-out.

Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.

See your agent think. Zero-config observability & governance for 30 AI agent runtimes: Claude Code, OpenAI Codex, Hermes, OpenClaw & 26 more. Live token costs, sessions, tool calls, crons.

LeanCTX — Context Intelligence for AI systems.

Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.

Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.

Make your AI coding tools work as one team. Route jobs across Claude, Codex, Cursor, Devin, Gemini, OpenRouter, and local models, carry your setup with them, and track every cost.

The design layer for agentic AI — design context, interface checks, and verification for coding agents.