Tagged “context-engineering”
8 listings
Servers

headroom
Updated todayCompress 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.

lean-ctx
Updated todayby yvgude
Control what your AI can see. LeanCTX (Lean Context) is the context intelligence layer for AI agents — one local Rust binary that decides what they read, remembers what they learn, guards what they touch, and proves what they save. 60–90% fewer tokens as the receipt. 76 MCP tools, 30+ agents, local-first.

neo
Updated todayby neomjs
Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

ripwire
Updated todayby redhat-et
ripwire — the ripgrep of AI context. A zero-dependency C++23 CLI that maps any codebase into a ranked, deterministic call graph for coding agents: orientation, blast radius, tests-to-run and quality verbs, plus an MCP server. ripgrep-fast retrieval, a tripwire on every claim it emits.

rosetta
Updated todayby griddynamics
Enforce organizational standards across every AI coding agent

FixMap
Updated 2d agoLocal-first repo maps for coding agents—ranked files, test routes, risks, CLI/MCP/GitHub Action, and public GitHub URLs.

gaius
Updated todayby jkubo
Self-hosted, self-correcting memory consolidation for AI coding agents: an open take on agent 'dreaming'. Extracts, ranks, and injects ops knowledge across Claude Code, Gemini CLI, Grok Build, and Codex sessions. Hybrid BM25 + sqlite-vec corpus, MCP server, fully offline.

diffctx
Updated todayby nikolay-e
Smart git diff context for LLMs and AI agents — selects the minimal code fragments needed to understand a change, under a token budget. Deterministic, local, MCP server included. Also exports a full codebase to YAML/JSON/MD.