Compress tool outputs, logs, files, conversations, and RAG context before they reach the model. On measured workloads, Entroly reduces unnecessary tokens by up to 90% while preserving answer-critical evidence through budget-aware selection, content-addressed recovery, and auditable Context Receipt. Works with Claude, Chatgpt/Codex,Openclaw.

Context intelligence layer for LLM agents: persistent memory with write-time dedup, sensitivity tagging, conflict detection, and hierarchical decay. ~12ms. No LLM calls. MIT.

Official Edgee CLI to interract with Edgee's Agent Gateway. Route Claude Code, Codex, Cursor, VS Code + Copilot, and more through Edgee's hosted gateway to cut token spend.

The open source, no-code MCP Server for AI-Native API Access

The Distillery. A Token Optimization Proxy

⚡ Cut Claude token usage by 90%+ — free, open-source, local-first context compression for Claude Code. Hybrid RAG (BM25 + ONNX vectors), AST chunking, reranking. No API needed.

Save context for what matters. The last agent you'll ever need.

💰 Save money on AI API costs! 76% token reduction, Auto-Fix token limits, Universal AI compatibility. Cline • Copilot • Claude • Cursor

Claude Code skill for optimizing oversized CLAUDE.md files using progressive disclosure

Your AI forgets everything between sessions. This fixes that — 98%+ retrieval accuracy, 100% on LongMemEval, 99% token savings. 44 MCP tools. Fully local, zero cost.

CodeGrok MCP is a Model Context Protocol (MCP) server that enables AI assistants to intelligently search and understand codebases using semantic embeddings and Tree-sitter parsing.

Copilot Context Optimizer is a VS Code extension that gives GitHub Copilot specialized tools to analyze files and process terminal commands efficiently without overwhelming chat context. It extracts only specific information needed instead of dumping entire files or verbose outputs, keeping conversations focused on problem-solving.

Context-Optimized Memory Bank — Reduce AI token usage with structured documentation and cache-aware reading strategies

MCP servers as CLI tools — built for AI agents

Lightweight, agent-optimized database CLI with one-shot schema introspection, column profiling, and ERD generation.

The Universal Open Knowledge Format (OKF) Ingestion Compiler. Convert PDF, DOCX, Markdown, and HTML into structured, cross-linked RAG context graphs using Google Gemini.

⚡ ZeroToken Skill — 让 Agent 用最少的 token 做最准的事。提示词纪律规范：压缩无效上下文、无效解释、无效工具调用、无效输出，准确性不降。

🎯 Optimize LLM token usage by 70-90% with smart context ranking, reducing costs while maintaining quality and performance.

This repository introduces the Letta framework, empowering developers to build LLM-based agents with long-term, persistent memory and advanced reasoning capabilities. It leverages concepts from MemGPT to optimize context usage and enable multi-agent collaboration for real-world applications like research, HR, and task management.

MCP server — Compressed Knowledge Graph for the NVIDIA AI developer stack. 20 domains · 998 nodes · 4× F1 vs RAG · 11× fewer tokens · deterministic traversal.