Show HN: Cantrip – Agent-native GTM engine I built for solo technical founders

Hey HN — I'm Austin in Seattle, a solo technical founder with 20+ years of engineering experience and 4 years of biz/marketing. I've shipped a lot of software. Selling it has always been the hard part.

I see a lot of Indie Hacker / bootstrap founders follow the same arc: build something Your proud of, Google "how to find your first customers," get a wall of generic advice, context-switch between six tabs of ChatGPT conversations that forget everything by tomorrow, and eventually just go back to writing code because at least that feels productive.

I built Cantrip to fix this. It's a go-to-market engine — not a chatbot, not a consultant replacement, not an all-in-one platform that wants to own your stack.

What it actually does: You describe your product (paste a README, explain it in plain English, whatever). Cantrip builds a Context Graph — a persistent, structured map of your business: ideal customer profiles, pain points, value propositions, channels where your customers hang out, competitors, and experiments to validate your assumptions.

The system runs continuous gap analysis. No ICP defined? That's a gap. Competitors not analyzed? Gap. Channels identified but untested? Gap. Each gap becomes a prioritized opportunity with three options: let Cantrip research it with AI, get a context-rich prompt to use in any LLM, or fill in what you already know.

Everything AI-generated enters a review queue. Nothing is treated as ground truth until you accept it. The graph deepens over time — each cycle builds on the last.

What's technically interesting: Cantrip is agent-native from day one. Every capability is exposed as one of 17 MCP tools — cantrip_snapshot, cantrip_next, cantrip_review, etc. Any

MCP-compatible agent (Claude Code, OpenClaw, Cursor, custom workflows) can read and write to your Context Graph programmatically.

This means your coding agent can finish a feature, call cantrip_snapshot, discover no value proposition covers the new capability, call cantrip_next to find the gap, and surface it in your review queue — without you leaving your IDE. The Context Graph becomes shared state for multi-agent coordination, with human review as the trust boundary.

The daemon handles identity, auth, and credit gating transparently. Agents read .cantrip.json from the working directory — no project IDs as parameters, no auth ceremony. One API surface powers the MCP server, dashboard, and CLI with zero drift between interfaces.

Business model: Credits, not subscriptions. GTM work is bursty — intense before a launch, quiet for weeks. Credits match that reality. Every feature available from day one; credits unlock depth, not access. Reads are always free.

This is super rough around the edges but if you want to kick the tires on the MCP server or CLI, join the Discord and I'll give you some free credits if paying is a barrier.

I've seen some "Autonomous company" launches, this isn't that. Check out the FAQ...

I'd genuinely love feedback on the architecture, the MCP tool design, or the overall approach. What am I missing? What would make this useful to you?