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AI DEVELOPMENT WORKSPACE · OPEN BETA v0.1.3

From idea to commit.
All in Minnow.

Plan a change, build it with agents, and review the diff in one desktop app. Your code, issues, and project notes give the agent the context to carry the work through.

Free and open source. No Minnow account. Local or cloud models.

INSIDE MINNOW A failing test, a one-file fix, and the diff ready to review.

ONE WORKSPACE, BY DESIGN

Built together.
From the ground up.

Your code, issues, changes, and project knowledge belong in the same place. In Minnow, they’re built into the workspace your agent works in.

See how the work flows

Code

The implementation

Issues

The work ahead

Git

The changes

Brain

The decisions

One shared workspace

The same project. The same agent. Context that carries forward.

THE BUILD LOOP

From one sentence to a merged change.

One conversation plans the work, runs it, shows you the diff, and remembers what it learned for next time.

  1. Step 1 Describe the change

    Write what you want in plain language. No ticket template, and no other app to open first.

  2. Step 2 Review the plan

    Plan mode has no tools that edit code, so nothing in your repo changes while you read. Adjust the plan, and approve it when it's right.

  3. Step 3 Let the agents work

    The plan becomes a board of Builder and Tester tasks, each on its own branch in a separate worktree, so your checkout stays clean. Their shell commands still run on your machine; turn on the agent sandbox for unattended runs.

  4. Step 4 Review the diff

    Changes come back as a diff with the tests already run. Commit it, open a PR, or send it back.

  5. Step 5 Keep what mattered

    Decisions go into Brain and bugs go into Issues, so the next run starts with that context.

THE APPS

Get to know your workspace.

Start in Code. Review in Source Control. Keep decisions in Brain. Explore the tools your agent can use without leaving the project.

01 · Code

The editor and the agent work on the same repo.

File tree, LSP, inline completion, Quick Edit, terminal, dev servers, and a Chromium preview.

Chat works directly on the repo, so the agent edits the file you're looking at and shows you the diff first.

  • LSP
  • inline completion
  • Quick Edit
  • terminal
  • dev servers
02 · Source Control

Git without leaving the workspace.

Review changes, history, branches, stashes, worktrees, pull requests, and CI.

The agent can commit and open PRs. You still decide what ships.

  • changes
  • branches
  • worktrees
  • PRs + CI
03 · Orchestrator

Turn a plan into parallel agent work.

A plan becomes waves of Builder and Tester tasks.

Each task runs in its own worktree and reports progress to the board. Nothing merges until you approve it.

  • plan → waves
  • Builder + Tester
  • worktrees
  • merge on approval
04 · Models

Run local models, cloud models, or both.

Hardware-fit scoring tells you whether a model will run well on your machine before you download it.

llama.cpp and MLX are built in, cloud providers use your own key, and routing assigns models to roles.

  • hardware fit
  • llama.cpp + MLX
  • cloud providers
  • per-role routing
05 · Brain

Your project gets a memory.

Brain is a Markdown knowledge base with semantic search, a code index, and memories the agent reads and writes.

Every page is a file on your disk. What one session works out, the next one starts with.

  • Markdown wiki
  • semantic recall
  • code index
  • memories
06 · Issues

The agent files what it finds.

List, board, triage, and saved views, plus issue tools the agent can use.

If an overnight run hits an edge case, the issue is waiting for you in the morning with steps to reproduce.

  • list + board
  • triage
  • saved views
  • agent-filed
07 · Scheduler

Put repetitive work on a schedule.

Run agent jobs on an interval or a cron schedule, scoped to a workspace, with a history for every run.

Jobs run while Minnow is open and pause when you close it.

  • intervals + cron
  • run history
  • workspace scope
  • /loop
  • /goal

Bring your model.

Cloud models, local models, or both. Choose how you connect.

Connect a cloud provider

Use models hosted by a provider with your own API key or provider account.

Connect a local app

Already running models on your computer? Connect Minnow to your local server.

Run models inside Minnow

Use your own hardware with built-in runtimes. No separate model app needed.

No Minnow account. No Minnow subscription. Minnow puts no cap on usage. Cloud providers set their own prices and limits.

FEATURES

Built in, across the whole workspace.

Every surface shares the same agent, tools, and models, so these work the same wherever you are in the app.

  • Modes

    General, Build, Plan, and Debug. Each mode sets the prompt and decides which tools exist at all, so Plan mode can't edit your code.

    Learn more →
  • Sub-agents

    Hand a job to a sub-agent: explore the codebase, run shell commands, debug a failure, or write up an issue. It works in the background and reports back, so your conversation stays short.

    Learn more →
  • Permissions

    Every built-in tool can be set to Full, Ask, or Off. Each call shows up in the transcript as it happens.

    Learn more →
  • Skills

    Reusable workflows like code review, opening a PR, and writing tests. Type / to run one. Each is a Markdown file you can edit or copy.

    Learn more →
  • MCP and plugins

    Connect any MCP server or local plugin. Their tools follow the same permission rules as the built-in ones.

    Learn more →
  • Code intelligence

    The agent can map the repo, find symbols and their callers, and read LSP diagnostics instead of searching text blindly.

    Learn more →
COMPLETELY YOURS

Your data is just files.

Chats, settings, memories, and downloads live under ~/.minnow, as Markdown, JSON, and SQLite.

Nothing is locked in a format only Minnow can read.

  • Edit anything by hand

    Skills, permissions, rules, and prompts are plain text. Edit them in any editor and the next session picks up the change.

  • See what the model sees

    Mode prompts and Quick Edit prompts are files too, so you can read exactly what gets sent to the model and change it.

  • No telemetry. No account.

    Minnow collects no telemetry and needs no Minnow account. API keys are encrypted on your disk. Cloud models receive the prompts and context sent to them.

  • Put it under git

    ~/.minnow is just a directory. Make it a repo and your prompts, skills, and settings get a history. Leave .key, providers/, search.json, and models/ out: they hold your credentials and gigabytes of model weights.

        ~/.minnow
├── .key
├── config.json
├── tools.json
├── sessions/
├── brain/
├── issues/
├── prompts/
├── skills/
├── providers/
└── models/
      

The point of a dotfile is that you can open it.

FREE

Free, with nothing held back.

There's no Pro tier, no per-seat pricing, and no feature that unlocks when you pay.

Minnow is licensed under AGPL-3.0-or-later. Every release stays open source, and anyone who ships a modified version, even as a hosted service, has to publish their source too.

The model

Minnow follows Blender's funding model: the full product is available to everyone, supported by people who use it.

Sponsoring supports the work. It doesn't unlock anything extra.

FAQ

Things worth knowing before you download it.

What is Minnow?
Minnow is a desktop development workspace with an agent built in. The editor, git, issues, planning, project notes, scheduling, and model hosting share one context, so the agent can work across all of them. It's free, open source, and built for one person on one machine.
Do I need an API key?
No. Use a local model through llama.cpp, MLX, LM Studio, or Ollama without a cloud account or API key. For a cloud model, connect your own provider key. The provider bills you for that usage; Minnow adds no subscription or markup.
What hardware do I need?
Minnow runs on 64-bit Windows 10 or later, macOS 12 or later on Apple Silicon, and 64-bit x86 Linux. With a cloud model, any machine that runs the app is enough. For local models, memory is what matters: the Models app checks your CPU, RAM, and GPU and scores each model by how well it will fit before you download it.
Does my code leave my machine?
Only where you send it. With a local model, prompts and code stay on your machine. With a cloud provider, that provider receives your prompt and the context you include. Minnow also connects out when you ask it to: web searches and page fetches, Hugging Face downloads, GitHub through your gh CLI, MCP servers you add, webhooks you configure, and update checks against GitHub Releases. There's no telemetry.
How is Minnow different from an AI code editor?
Editors like Cursor, or VS Code with Copilot, put an agent in the editor. In Minnow, the editor is one part of a larger workspace, so the agent working in a file can also read the related issue, check the branch, look up past decisions in Brain, and file what it finds.
Can my team use it?
Everyone on a team can install their own copy, and the license allows it. Minnow is built for one person on one machine, though: there's no shared workspace, admin console, or SSO. Where a feature could be built for solo use or for teams, the solo version came first.
What does AGPL mean for me?
You can run it, read the source, change it, and fork it. If you distribute a modified version, or run one as a network service for others, you have to share that source under the same license. If you're just using Minnow on your own code, the license doesn't ask anything of you.

Open a repo and start building.

Available for Windows, macOS, and Linux. No account needed, and no API key if you use a local model. Minnow is in open beta, so expect frequent updates.

git clone https://github.com/HenriGrimm/Minnow.git