MimiWork

The AI coworker that hands you the finished file.

Not a chat window. A colleague who reads your folder, does the work, and saves a .docx, .pptx or .xlsx you can send — on your machine, with your model key, asking before anything consequential.

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The difference in one line

"Summarise these three PDFs into a one-page brief."

Most assistants: a summary in the chat, which you then paste into Word and format. MimiWork: brief.docx in your folder — PDFs actually read, tables extracted, numbers carried across, formatting intact.

That's the whole idea. Ask for an outcome, get the artifact.

Why it feels different

Actually agentic. Not a chat window with tools bolted on: Mimi plans the work, reads the files, runs the analysis, checks its own layout, and iterates until the file is finished — dozens of steps from one ask. Plan mode shows you the whole approach before anything runs.

It learns as you work. Memory keeps what it noticed about your projects. Skills package your know-how once — brand rules, methods, house style — and apply forever. Instructions set standing rules per folder. Week two is visibly better than week one, and everything it learned is yours to read, edit, or delete.

Steerable while it works. See it heading the wrong way? Just type. Your correction lands at the next safe step without restarting the work — and a looping model is stopped before it burns your credits.

It runs while you don't. Say "every Monday at 8…" in plain words and it becomes a local automation with a full transcript; anything needing a decision waits in your Inbox instead of guessing.

Yours, on your machine. No vendor cloud, your model keys, every consequential action approval-gated, and Mimi's file tools can't reach outside the folders you grant.

What it actually does

One coworker, three trades. There is no mode to pick — Mimi carries all of this into every conversation and reaches for the right craft when the work calls for it.

	What it produces
Data analysis	Profiles the dataset before touching it — SPSS/Stata variable and value labels included, so q4_1 becomes "Satisfaction with onboarding, 1–5" — runs the analysis in a persistent Python kernel or R, and reports sample sizes, effect sizes and assumption checks, not just p-values.
Documents	Drafts and revises Word documents in place without wrecking your formatting — headings, tables, comments and all — and can leave real tracked changes with a plain-language "what I changed and why".
Decks	Turns findings into a 16:9 PowerPoint that argues a case — every slide titled with its takeaway, not its topic, and built from a real layout vocabulary (a single claim, a big number, a participant's own words, a side-by-side, a chart) rather than slide after slide of bullets. Charts come from your actual numbers, and speaker notes come with it. Text is measured and fitted so nothing walks out of its frame. Point it at your house template and it uses your brand instead.

It reads what work actually arrives in. PDF (with table extraction — and an honest warning when a document is scanned rather than silently returning nothing), Word, Excel, PowerPoint, CSV, SPSS .sav, Stata .dta, and images it can crop, annotate and combine into figures.

Teach it your way once. Package your brand colors, fonts and house rules into a skill and every deck, document and spreadsheet comes out in them without being asked. Browse 8,400 community skills by shelf, and read a skill's real instructions — and which tools it wants — before it ever lands on your disk.

It connects to where you work. 25+ integrations — Slack, Outlook, Google Drive, GitHub, Jira, Notion, Linear, HubSpot, Canva, monday.com — plus anything reachable over MCP. Tag it in a Slack channel and the finished work comes back as a thread reply. Canva signs in with one click and Mimi can search, generate, edit, comment on and export your designs there.

It can run a team of coding agents. With Claude Code, Codex, opencode, Cursor or Gemini CLI installed, Mimi hands software work to them, and can put several on one job: each agent gets its own part on its own git branch, one can review another's branch, and Mimi passes what one found back to the others as feedback until the work is right. Merging a branch into yours goes through the same approval as any other command. Connectors ▸ Coding agents shows whether each is installed and signed in, tests it with one small call, and picks its model: the latest by default, or one from the agent's own list. Claude Code and Codex run on your own Claude or OpenAI account; opencode runs on its newest free model unless you pick one from the providers you set up in it; Cursor and Gemini CLI run on your own Cursor or Google account. None of them uses QualiTaTi credits. opencode, Cursor and Gemini CLI do not stop to ask before they edit files or run commands in their folder, so Mimi still asks you before every hand-off. While Mimi coordinates agents in a chat, the side panel lists each one with its model, so you can change a model without leaving the conversation.

Including where your data lives. Connect Qualtrics and ask for the December wave: it reads the questionnaire so Q4_1 arrives as "How satisfied were you with — speed of setup", then downloads the responses as a CSV or a labelled SPSS .sav in your folder, ready for the analyst. It never edits or sends anything in Qualtrics, and the download itself asks you first.

It runs while you don't. A Monday brief, a weekly report, a standing watch on a channel: automations run locally with full transcripts, and anything needing a decision waits in an Inbox instead of guessing.

You can steer it mid-run. Notice it heading the wrong way? Just type — "use the December wave, not November" lands at the next safe step without stopping the work, and a looping model is caught and stopped before it burns your credits.

It checks in before acting. Sends, writes, shell commands and external data pulls are approval-gated. Plan mode proposes first and runs nothing until you say go.

What you learn here works everywhere

MimiWork deliberately borrows the vocabulary and the gestures of Claude Code, Claude Cowork and Codex — so the habits transfer in both directions, and nothing you learn is trapped in one app.

In MimiWork	Cowork	Claude Code	Codex
/ — app commands, your saved commands, your skills	/ commands	slash commands	/ commands
@ — point at a file in a granted folder	@ mentions	@ mentions	@ mentions
Default · Accept edits · Plan (⇧⇥ cycles; Bypass is a menu pick)	Manual / Auto / Skip	plan / default / bypass	plan / approval / auto
AGENTS.md — and CLAUDE.md is read too	folder instructions	CLAUDE.md	AGENTS.md
Skills — SKILL.md folders, importable from ~/.claude/skills	Skills	Skills	—
Projects — folder + instructions + memory + threads	Projects	a repo you cd into	a repo you cd into

Settings ▸ Transfer guide keeps the full map one click away.

Bring your own model — no lock-in, no markup

Paste your own key and switch anytime:

OpenAI · Anthropic · Google Gemini · DeepSeek · Qwen · Kimi (Moonshot) · GLM (Z.ai) · MiniMax · Mistral · Grok (xAI) · Inkling — open-weight models via Together and Fireworks, AWS Bedrock, and fully local via Ollama.

Or skip keys entirely: sign in with your QualiTaTi account and the "Mimi" models spend your existing credits — nothing to configure. The Activity page shows exactly what each call cost and which pool paid — the numbers come from the server's own ledger, not a local estimate. A switch in Settings picks where the models run: US (cheaper credits) or strict-GDPR Paris (data stays in Europe). Signing in also opens your QualiTaTi research data: ask for a project, an interview transcript or a survey's responses and Mimi can pull them in to analyse — each retrieval asks your approval first, and nothing is fetched on its own.

Install

The app updates itself from then on.

Your machine	Download
Mac — Apple Silicon (M1–M4)	MimiWork-macos-arm64.dmg
Mac — Intel	MimiWork-macos-x64.dmg
Windows 10/11	MimiWork-windows-setup.exe

Starting with v0.6.15, Windows installers are signed by QUALITATI, and both Mac builds are signed by Fengming Liu and notarized by Apple. Publisher signatures identify who distributed the app and protect its integrity. New Windows downloads can still receive SmartScreen reputation warnings, and company device policies still apply.

Mac — the first launch

1. Download the Apple Silicon or Intel .dmg for your Mac.
2. Open it and drag MimiWork into Applications.
3. Open MimiWork from Applications. macOS may ask you to confirm opening an app downloaded from the internet.

If macOS reports a damaged app or a security block, download the latest release again and contact support or your IT team if the problem persists. Do not disable Gatekeeper or remove security protections to install it.

Windows — the first launch

1. Download MimiWork-windows-setup.exe.
2. Right-click the file and open Properties ▸ Digital Signatures to check the QUALITATI publisher signature.
3. Run the installer and follow its prompts. MimiWork opens when installation finishes.

If Windows or your browser blocks installation, check the exact warning and contact support or your IT team. A signed installer does not override organizational policy.

Every release is on the Releases page. Versions before v0.6.15 may have different signing status; use the latest verified release.

The ten-minute tutorial

The one habit that matters most: ask for the outcome, not the steps. "Read these transcripts and write me a themed summary as a Word doc" gets you summary.docx. "Can you help me analyse interviews?" gets you a conversation. (One page: docs/TUTORIAL.md — also in 中文, Norsk, Français · Illustrated PDF, 13 pages: docs/MimiWork-Tutorial.pdf)

1 · Connect a model — QualiTaTi credits or your own key (2 minutes)

Open Settings ▸ Models. Two ways in:

• Sign in with QualiTaTi — no keys; the Mimi models spend your existing credits. The card shows the four tiers — Mimi Puppy (free, fastest), Mimi Hound (free, robust), Mimi Wolf (powerful), Mimi Werewolf (frontier) — each with a Test button that makes a real call. While you're here: pick your model region (Default · US, cheaper — or Strict GDPR · Paris, data stays in Europe), and know that the Activity page shows exactly what each call cost, from the server's own ledger.
• Paste your own key — OpenAI, Anthropic, Gemini, Kimi, DeepSeek, Mistral and more, or fully local via Ollama. Switch anytime from the composer.

2 · Give it a folder — the one real setup decision

Click the folder starter card, or just ask "work in my Projects/interviews folder". Mimi's file tools can't read outside the folders you grant — so grant the folder where the real files live. Click a folder's name under Access to open it in Finder/Explorer.

3 · The first real task — and what to expect while it runs

Read the three PDFs in this folder and write a one-page brief as brief.docx — keep the numbers in a table.

Turn results.xlsx into a 10-slide deck that argues we should fix mobile first. Speaker notes for my co-presenter.

While it runs: anything consequential asks first (approval cards); you can steer without stopping — type "use the December wave, not November" and it lands at the next safe step; drop files straight into the chat — from a granted folder they become @mentions worked on in place, from anywhere else they're copied visibly into the session's folder. Finished files land in your folder; the Files page keeps every deliverable in one place.

4 · Three keys — /, @, ⇧⇥

Key	What it does
/	App commands (/plan, /compact, /init, /model…), your saved commands, your skills
@	Point at a file in a granted folder — no path typing
⇧⇥	Cycle Default → Accept edits → Plan. Bypass permissions is a deliberate pick from the mode menu, never a keystroke

For anything with stakes, hit ⇧⇥ into Plan first: Mimi proposes the whole approach, you approve or redirect, then it runs. Same gestures as Claude Code / Cowork / Codex — Settings ▸ Transfer guide has the full map.

5 · Teach it your way — once — instructions, skills, memory

• Instructions (Settings ▸ Instructions, or AGENTS.md/CLAUDE.md in the folder): standing rules. "Reports in UK English. Stats always with effect sizes."
• Skills (Settings ▸ Skills): package your brand rules or methods once; every deck and doc comes out in them without being asked. Browse 8,400 community skills, read a skill's real instructions before installing, import from ~/.claude/skills.
• Memory (Settings ▸ Memory): what Mimi noticed and kept — review, edit, delete.

6 · Connect where you work — Slack, Qualtrics, QualiTaTi data, 25+ more

The Connectors page: Slack (tag Mimi in a channel, work comes back in-thread), Outlook, Drive, GitHub, Jira, Notion, Canva — and Qualtrics: read a questionnaire so Q4_1 becomes a real question, pull responses as CSV or labelled SPSS .sav, with your approval per download. Your QualiTaTi research data works the same way. Anything else speaks MCP.

7 · Make it run while you don't — automations and the Inbox

Every Monday at 8, read the new files in field-notes/, and put a one-page weekly summary in reports/.

That becomes an Automation — local, full transcript, and anything needing a decision waits in your Inbox instead of guessing.

8 · A good week, in five asks

1. "Work in this folder. Profile every .sav in it and give me a data dictionary as a Word doc."
2. "Package our brand guidelines into a skill."
3. "Turn the wave-2 findings into a 12-slide deck for the steering committee." (in Plan mode)
4. "Pull the December survey from Qualtrics as SPSS and test whether satisfaction differs by channel — effect sizes, not just p-values."
5. "Every Friday at 4, summarise this Slack channel's week into a memo in reports/."

By Friday: a data dictionary, an on-brand deck, a real analysis, and a standing automation — every file on your disk, made with your keys, under your approval.

Privacy

MimiWork is fully local: the agent loop, your conversations, connector tokens and model keys all live on your machine. With your own model key there is no vendor cloud in the loop — no hosted sign-in, no OAuth broker, no relay. A QualiTaTi account is the one opt-in exception: its sign-in and its model gateway are hosted. Connectors use your own credentials (or a vendor's own local OAuth); your data leaves the machine only through the model and integrations you choose.

What approving code grants. Folder grants bound Mimi's file tools. Shell commands and Python or R code you approve run as your user account, so they can reach whatever your account can. Read what a command does before you approve it, and keep Bypass permissions for folders you would hand over anyway.

Quality

The test suite is part of the product: 1,507 backend tests cover the agent engine, tools and connectors — including that every Office tool registers a schema a real provider accepts, that code execution is approval-gated like the shell, and that a scanned PDF is flagged rather than silently summarised from nothing. The desktop app carries 230 GUI unit tests and 150 hermetic Playwright e2e tests (mocked backend, no network), with a separate live suite for the real thing. ruff and eslint gate CI alongside them.

Build from source

┌────────────────────────────────────────────────┐
│               MimiWork desktop app             │  native shell + GUI (Tauri + React)
├────────────────────────────────────────────────┤
│           local agent server (Python)          │  engine · tools · connectors
├───────────────┬────────────────┬───────────────┤
│  your files   │   your tools   │  your model   │  everything runs with your keys,
│  & terminal   │ 25+ connectors │  any provider │  on your machine
└───────────────┴────────────────┴───────────────┘

Prerequisites: Python 3.10+, Node 20+, Rust via rustup, and cmake (brew install cmake).

git clone https://github.com/lanceyuu/mimiwork
cd mimiwork

# 1. One-time bootstrap — creates the Python venv at .venv
bash packaging/setup_dev_env.sh

# 2. Start the local agent server
.venv/bin/openworker-server --cwd ~/some/project --port 8765

# 3. In a second terminal, start the UI
cd surfaces/gui
npm install
npm run dev        # browser UI on the Vite dev port

For the full desktop app, replace step 3 with npm run tauri dev; build an installable DMG with packaging/build_dmg.sh.

Directory	What's in it
coworker/	Python backend — agent engine, model providers, office/PDF/image/analysis tools, connectors, MCP client, automations
surfaces/gui/	Desktop app — React UI + Tauri shell
stt/	Speech-to-text sidecar (Rust) for voice input
packaging/	Installer builds (macOS DMG, Windows), dev bootstrap
docs/	Design specs and decision logs
tests/	Backend test suite

Acknowledgements

MimiWork is a fork of OpenWorker by Andrew Ng and contributors, built on aisuite. The repetition-guard detection (stopping a looping model before it burns your credits) and the steer-while-running interaction are adapted from ideas in FrontierAgent by Apodex AI (Apache-2.0); the search deduplication and dead-end guidance in the web tools adapt the rollback observers of AgentHarness (Apache-2.0) to a desktop where the user pays per model call. The markdown /command files with $ARGUMENTS and the plugin-style tool hooks follow opencode's conventions, and the /, @ and Shift+Tab gestures deliberately match Claude Code and Claude Cowork so the muscle memory transfers. This fork repositions the tool for knowledge work — Office deliverables, PDF and image handling, and a statistics-aware data-analysis toolchain — and carries its own desktop refinements. Internal binary and package names (coworker, openworker-server) keep their upstream names for compatibility.

The full list of projects, skills and libraries MimiWork learns from or ships with — and what was taken from each — is in CREDITS.md, and in the app under Settings → About.

License

Personal and business use are allowed. Creating another application from covered MimiWork-specific code requires permission — see LICENSE. OpenWorker and other third-party components retain their own licenses; see THIRD_PARTY_NOTICES.txt. Original work © 2024 Andrew Ng; modifications © 2026 MimiWork contributors.