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4 repositories · updated 2026-11-06
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1headroomlabs-ai / headroomAuthor description: Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.PythonApache-2.0 · PermissiveInsufficient rank history79,009
2microsoft / TokenEconomizerExperience-Driven Black-Box Cost Control for Coding AgentsPythonApache-2.0 · PermissiveInsufficient rank history4,423
3juyterman1000 / entrolyCut 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.PythonApache-2.0 · PermissiveInsufficient rank history483
4activeing123 / mcptoonAuthor description: One zero-dependency MCP gateway CLI for every server and agent skill. Token optimization, tool discovery and context compression: 71,929 -> 581 tokens (-99.2%, measured), schemas stay out of context. One config for Claude Code, Codex, Cursor, every agent. 561KB, pure Python. | Zero-dependency CLI: Manage all MCP tools and skills, tool discovery saves 99.2% token.PythonApache-2.0 · PermissiveInsufficient rank history422
