Remarc – contextual feedback for coding agents via MCP

Like any side project, Remarc had its innocent beginnings in my own problem — there was no good way to provide contextual feedback to AI agents on their own output.

There are a plethora of tools for collaborating with humans, but surprisingly little for collaborating with AI. Chat just wasn’t cutting it for the kind of contextual feedback I wanted to give my agents.

This thing in the implementation plan? Change it to that. What did you mean here? See this button? Here’s a screenshot, I circled it — it’s missing a hover state. This sentence in the 3rd paragraph? Rephrase it.

If you’re an opinionated builder who wants things in a very specific way, this quickly becomes a nightmare. You either end up dictating paragraphs of messy feedback or resolving everything one by one. AI is great at parsing mess, but garbage-in-garbage-out still applies.

And that’s where I found myself. I could easily get products to 90%, but that last 10% of polish that makes them actually stand out was unnecessarily clunky.

Building with AI has a last-mile problem. So I decided to build something for myself.

Remarc lets you comment on anything on your screen - select any text, any web element, take a screenshot, and leave a comment. Each comment has a status and goes into a session that your agent can start / read / update. Your feedback is now structured and contextual. Comes with webhooks and lots of other bells and whistles so you can dial it in for yourself if this is the way you like to work. Free and open source.