GCF Python implementation. 100% LLM comprehension on every frontier model. 50-92% fewer tokens than JSON. 43B+ round-trips verified. Zero dependencies.
A thin MCP client for humans and agents — run any Model Context Protocol server, call its tools, read its stderr, and reconnect after each edit. REPL, headless CLI, or an MCP server your agent drives. No client config edits, no restarts.
dst (data serve tool) — open-source semantic layer and MCP server between the AI your team uses and your data warehouse. Governed answers with the SQL, a grade and a receipt.
Roblox Studio MCP server & plugin for Claude Code, Cursor, Codex, and Gemini. AI-powered scripts, terrain, assets, lighting, and bidirectional project sync.
Self-improving context & memory for Claude Code and OpenAI Codex. One canonical knowledge store injected only when relevant — hooks push budgeted context, an MCP server serves depth on demand, and it learns lessons from your sessions. Agent memory + context engineering as a single static Go binary.
Interactive question boards & HTML idea visualization for AI coding agents (Claude Code, Codex, …) — ask users structured questions in the browser, await submit, get JSON. Zero deps.
Call dibs on files. Coordination for parallel coding agents — file claims with expiry, enforcement hooks, and git-native lessons. One binary, no server, no database.
Open-source Vibe Testing suite: an MCP server for the coding agent you already run, a VS Code review cockpit, and CI. Your agent explores your app and crystallizes each flow into a plain @playwright/test spec you own — record == replay, runs in CI with zero AI.