v1.8.1 · Desktop app for Mac, Windows & Linux

See where your prompt
breaks across models.

Run the same prompt across Claude, GPT, Gemini, and your local models at once. See every answer side by side, get one score for how much they agree, and catch the failures before your users do — privately, on your own hardware.

Local-first MIT licensed Works offline
prompt › Summarize this contract clause in one sentence.
Claude
answered · 1.2s
GPT
answered · 0.9s
Gemini
refused · added caveats
Divergence: 42% · Mixed
Same prompt. Three answers. One refused. You'd never see this with a single model.
Run Across Models — outputs side by side with a divergence verdict
The problem

The same prompt rarely behaves the same way twice.

Most teams never find out until production — when a customer does.

ON GPT
It succeeds
Clean, confident output. So you ship it — assuming every model behaves the same.
ON CLAUDE
It hallucinates
Fills the under-specified gaps with plausible-sounding details that aren't true.
ON GEMINI
It refuses
Reads an ambiguous instruction as unsafe and declines — or buries the answer in caveats.
ON LOCAL
It breaks
Ignores the format you asked for and returns something your parser can't read.

Amagra shows you all four before deployment — running your prompt everywhere at once and scoring exactly where the models disagree.

What it is

A debugger — for prompts.

You already know this loop from code: install, paste, run, see the errors, fix, run again. Amagra is that exact loop for the prompts you write — same muscle memory, no cloud.

The loopVS Code + PythonAmagra
Get itInstaller · ~300 MB · ~5 mindocker pull d4shm1r/amagra
RuntimeInstall the Python extension first Local model included — zero key, offline
New fileOpen test.py, paste codeOpen the debugger, paste your prompt
See problemsHit Run → 10 errors printBefore you run — health score + role / task / format checks
FixEdit all 10 by hand One-click auto-repair, checks turn green live
Run▶ → one outputRun across models — Claude / GPT / local, side by side
Read resultOutput is outputOutputs + latency + a divergence verdict

VS Code tells you your code is broken. Amagra tells you your prompt is under-specified — and runs it across every model so you see exactly where they disagree.

How it works

From prompt to verdict in seconds.

Paste once, run everywhere, read one answer instead of three.

1
Paste your prompt
Drop in the prompt you're shipping. Instant checks flag what's under-specified before you spend a single token.
2
Pick your models
Claude, GPT, Gemini, and any local Ollama model. Cloud is opt-in with your own key; local runs fully offline.
3
Run across all of them
One click sends the same prompt everywhere. Answers come back side by side with latency and length.
4
Read the divergence
One verdict — Aligned, Mixed, or Divergent — tells you at a glance whether it's your prompt or the model.
# Prefer the terminal? Run from source with Docker
git clone https://github.com/d4shm1r/amagra
cd agentic-ai && cp .env.example .env
docker-compose up

# → Dashboard: http://localhost:3000
Built in the open

Nothing hidden. Yours to run.

An open architecture with a documented API — see exactly how every decision was made.

Free
Self-hosted forever
10
Specialist agents
100+
Documented API endpoints
5
Model providers
MIT
Open source license
And there's more under the hood

A debugger on the surface. A workspace behind it.

Debugging prompts is the way in. Once you're inside, Amagra keeps working for you — routing, remembering, and recording every decision it makes.

Persistent memory
Semantic memory across sessions. It remembers your projects, decisions, and the lessons you've taught it.
Glass-box observability
Every routing decision is logged and replayable. Trace exactly why the system chose what it chose — not a black box.
Specialist agents
Ten domain experts — Python, web, DevOps, data, and more — dispatched automatically, running privately on your hardware.
Plan graph Decision replay Event log Memory browser Step verification Learns from feedback
Download

Install in a minute. No cloud account.

One download, double-click, done — the backend and UI ship together and run entirely on your machine.

macOS
.dmg · Apple Silicon & Intel
Download
Windows
.exe installer · 64-bit
Download
Linux
.AppImage · one file, no deps
Download

Unsigned for now, so first launch shows a Gatekeeper / SmartScreen prompt — open anyway. Prefer to run with Docker or build from source →

Pricing

Start free. Pay when it saves you time.

The self-hosted version is free forever. Managed plans add hosting and a frontier-model backend — no GPU required.

Self-Hosted
$0
Run on your own hardware with your own models. Full access, no limits.
  • All specialist agents
  • Local model (4GB VRAM)
  • Unlimited queries
  • Full memory + learning
  • Plan graph, replay, event log
  • Managed hosting
  • Claude / GPT-4o backend
Get the code
Team
$249/mo
2–10 users with shared cognitive state. One engineer's context improves the whole team.
  • Everything in Developer
  • Up to 10 users
  • Shared world model
  • 50,000 queries / day
  • Team memory namespace
  • Cognitive Ops audit trail
Contact us
Common questions

Questions before you download?

Privacy, supported models, pricing, and exactly how the divergence score is computed — all answered in full on the FAQ page.

Read the FAQ →
Open source · Self-hosted · Private

Your AI. Your hardware. Your data.

The self-hosted version is free forever and runs on hardware you already own.