dmx vs Wattfare

dmx is an open source AI-native engineering harness. It runs as an MCP server inside Cursor, Claude Code, Copilot, or any IDE that speaks the Model Context Protocol, and...

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you.

About dmx

dmx is an open source AI-native engineering harness. It runs as an MCP server inside Cursor, Claude Code, Copilot, or any IDE that speaks the Model Context Protocol, and wraps your AI workflows in structured, verifiable loops. The model is fast and often impressive, but the output is inconsistent. Quality depends on how you prompted, whether you remembered to run tests, whether the spec was clear before the first line of code was written. There's just you and the model and whatever happened to work that day.

About Wattfare

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you. OpenAI-compatible Works with the Vercel AI SDK ~5-min integration. One button connects a user's inference budget to your app, metered, capped, and revocable. The problem AI costs are the one line item you can't predict. Every AI app makes the same uncomfortable bet: price high enough to survive your power users, ration usage so nobody hurts you, or quietly lose money on the heavy ones.