Every leading AI provider, already wired in
Mulu builds the feature, runs the verification pipeline, and hands you the proof. Recorded browser testing, codebase-aware context, AI credits, and local-first project workflows in one desktop app.
Every leading AI provider, already wired in
Mulu does not stop when the code compiles. After it builds a feature, it opens the app, runs the flow, checks what happened, and records the verification run. You see more than a claim that it works. You get evidence.
That pipeline includes browser actions, visual checkpoints, console inspection, and a verification recording you can review. If a feature is supposed to click, type, submit, navigate, and render correctly, Mulu runs that sequence before calling the work done.
This is the product story. Other tools generate code and hand you the risk. Mulu builds, verifies, and shows the proof before you ship.
Most tools grep around the repo and hope they found enough. Mulu builds a live map of the codebase, ranks the files that matter, and understands which components, routes, handlers, and tests are connected before it makes the change.
That map is what makes the verification pipeline useful. The agent knows where to edit, which flows to exercise, and what collateral damage to watch for. Verification without context is just random clicking. Mulu is not guessing.
Context management is the second moat. It is the system underneath the proof: relevance ranking, dependency awareness, and impact preview working together so the right thing gets built and the right thing gets verified.
When something breaks, Debug Mode should not settle for "I think I fixed it." It now uses the same verification tools and workflow as build mode: apply the fix, rerun the flow, inspect the result, and record the proof again.
That means debugging is held to the same standard as shipping a new feature. If the bug was in a runnable path, the fix is not done until the verification pipeline passes. Manual confirmation is there when automation cannot prove enough, not as the default.
The result is tighter loops and less back-and-forth. Build mode and debug mode both end on evidence.
The verification pipeline is the lead story, but the rest of the coding loop is still here: editor, terminal, project memory, model routing, planning, debugging, and code review inside one workspace.
When your app needs a backend, connect services you own, such as Supabase. Mulu keeps the build loop fast without taking ownership of your hosting stack.
You keep the speed of an AI builder without giving up control of your infrastructure.
No hand-wavy "should work." Just describe what you want, review the proof, and keep building with the right local and connected tools.
Talk to Mulu or type in plain English. Say what you want in your own words and the app works out what you mean, asking follow-ups only when it matters.
Mulu breaks the request into tasks, makes the edits, then runs the verification pipeline. Browser flows, screenshots, logs, and recorded proof are part of the handoff.
If the run passes, you have evidence. When you need a public URL or backend, use your own hosting and Supabase project with normal environment setup.
A full AI coding system where the browser run, the codebase map, and the final proof are core product behavior, not an afterthought.
Mulu can open the app, execute the flow, inspect the result, and record the run. The feature is not done because the model says it is done. It is done when the evidence says it passed.
The codebase map surfaces the exact files and tests that matter before the edit or verification run starts.
Mulu knows what else is connected, so the agent can check likely blast radius instead of finding breakage later.
Tree-sitter and code graph signals give the agent real structure, not just filename matching and keyword search.
The same verification tools now back both new builds and bug fixes. If Mulu says the feature is fixed, there is a verification result and a recorded run behind that claim.
Other tools help write code. Mulu builds, verifies, and shows the evidence in one place.
| Mulu Code | Cursor | Claude Code | Lovable | |
|---|---|---|---|---|
| Recorded verification runs | Yes | No | No | No |
| Codebase map + impact preview | Yes | No | No | No |
| User-owned backend setup | Yes | No | No | No |
| Local-first project control | Yes | Yes | Yes | No |
| Multiple AI providers | Yes | Yes | Yes | No |
| Desktop app | Yes | Yes | No | No |
| Pay for what you use | Yes | No | Yes | No |
| Starting price | Free | $20/mo | Free + API | $25/mo |
Download Mulu Code free and have a working app in the time it takes to read the getting-started docs on any other platform.