SuperCompress: query-aware context cut for coding agents
At a glance
SuperCompress v2 compresses context against the query (keeps answer-critical lines verbatim): ~64% mean cut on their B5 coding-agent suite with 24/24 evidence-retention passes; MCP/plugin for Cursor/Claude Code/Codex plus hosted API and open weights. This workflow is listed under context-compression, token-efficiency, coding-agents, mcp, learnable-paradigm.
HN (Ted Haley): Pensieve locally indexes code, docs, and past agent sessions (watches repos/worktrees/uncommitted edits), exposes MCP search so Claude Code/Codex/Cursor get the few relevant passages with file:line instead of multi-round grep; Qwen3-Embedding-0.6B + SQLite/trigram + turbovec; macOS-focused OSS.
MCP-connected runtime QA maps critical flows and entry points, then re-tests the blast radius of each Claude Code/Cursor/Codex change against live Postgres/Kafka/APIs/MCP tools—contracts, authz, OWASP, errors—before merge, with self-heal when behavior changes on purpose.
Open-source local procedural memory that learns only after tests pass, then hands Claude Code/Codex/Cursor a short verified skill note on similar tasks (reported token/tool cuts in published benchmarks).
Magic Patterns’ MagicOS is an infinite canvas for PRDs, GitHub context, screenshots, and side-by-side UI variants; pick a winner and hand it to Claude Code, Cursor, Codex, or any MCP-compatible coding agent instead of losing the design journey in a linear chat log.