Context Cooler

Eliminate token burn with the coolest MCP on the net.
Burn fewer tokens. Ship cooler agents.

A standalone Model Context Protocol (MCP) server that gives any MCP-compatible coding agent — Claude Code, Cursor, OpenAI Codex CLI, Gemini CLI, OpenCode, Grok CLI, Shadow — a sandboxed runtime, an FTS5 knowledge base, and a multi-messenger delivery channel. Built from scratch on the MCP spec. Zero outbound dependencies beyond the four pinned ones in `package.json`. MIT-licensed, audit-readable end-to-end.

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The "Think in Code" philosophy

When an agent needs to analyse a directory, a JSON dump, or 47 source files, the temptation is to *Read* every file and let the model figure it out from raw text. That's how 750 KB of cached context disappears in a single afternoon: every turn re-pays the read cost.

**Don't pull data into the model. Push code at the data and pull back the answer.**

Canonical example

"Across these 47 TypeScript files, find every `await` that's missing a `try/catch`."

Approach	Bytes consumed	Tokens (rough)
Read × 47 (/src/**/*.ts)	~700 KB raw text in context	~175,000
ctx_execute (one shell+grep call, prints summary)	~3.6 KB summary	~900

The 195× reduction isn't theoretical — it's what a real morning-brief pipeline measures every day. The agent's job is to **write a script**, not to memor