Headroom
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.
Plugins Filament, packages Laravel et starter kits open source activement maintenus. Tous en MIT, avec des releases pour v3, v4 et v5 selon les cas.
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.
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
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.
Find the ghost tokens. Fix them. Survive compaction. Avoid context quality decay.
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
Tous les packages ont une CI, des tests Pest et des issues ouvertes taguées good first issue.
Nouvelle version disponible.