Run Browser Use on MIOSA
~15 min TypeScript PythonWhat you’re building: Install the open-source library and let an agent drive a real browser.
Primitives you’ll use: Computer, Sandbox
Agent prompt
Start with your coding agent
Choose how you will use it. The brief installs and runs the real tool on MIOSA, then shapes it for your team or your customers. Copy it into OSA, Claude Code, Codex, or Cursor.
Template coming soon1 What are you building?
Leave it empty and your agent will propose 3 names, pick one, and use it for resources, the domain and branding.
3 Configure
Reference tool
Browser Use, by Browser Use (https://browser-use.com): an open-source library that lets an AI agent drive a real browser.
How it works: You give the library a task and a model; it controls a Chromium browser (pages, clicks, forms, extraction) in a loop until the task is done.
Key capabilities:
An agent that drives a real browser
Extracts structured data from pages
Works with your choice of model
Open source and embeddable
You will install and RUN the real Browser Use (open source Python library). Read its docs first: https://docs.browser-use.com. Every install command below comes from them; if the docs and this brief disagree, the docs win.
How it runs on MIOSA
Where it runs -> a MIOSA computer (a persistent desktop with a browser)
State and files -> Scripts and outputs live in /workspace on the computer; browser profiles persist with the computer.
Model -> your own provider key, never a MIOSA platform key
Your customers -> one workspace each, isolated from each other
Goal
Install and run Browser Use on a MIOSA computer, so it can serve my customers. Each customer is isolated in its own workspace; I meter usage and bill them.
Product name: propose 3 product names, pick one, and use it for resource names, the domain and branding. Until you pick, <product-name> stands for it in the commands below.
Scale: a prototype.
Set up
npm i -g @miosa/cli
miosa login && miosa whoami
miosa api-key create <product-name>-key --preset agent
export MIOSA_API_KEY="msk_u_..."
miosa org
Resources
Sandbox: the agent's isolated Linux workspace
miosa create <product-name>-box --wait
Computer: a persistent Linux desktop with a browser
miosa computer create <product-name>-desktop
Auth and tenancy
Your organization is the platform; customers never get a MIOSA account, they sign into YOUR product. One workspace per customer, created as they onboard, isolates their machines, runs and data.
miosa workspace create <product-name>-customer-1
Tag every machine and run with the customer id in `metadata`, and never query across customers. Meter usage per customer with GET /api/v1/usage and set who pays with PUT /api/v1/bill-to (/docs/platform/usage-and-billing).
Install Browser Use
Run these inside the computer (its terminal), in order. The commands are from the official docs.
curl -LsSf https://astral.sh/uv/install.sh | sh
python3 --version # Python >= 3.11 is required
uv init --python 3.12
uv add browser-use
Check: the install finishes without errors; the next sections configure and start it.
Configure
Put your own model key in `.env` (the README example uses OPENAI_API_KEY). A MIOSA computer already has a desktop and Chrome for the agent to drive; use Browser Use's cloud browser only if you choose to.
Model: Anthropic (Claude). Calls use my own provider key (ANTHROPIC_API_KEY); MIOSA platform keys are never used.
export ANTHROPIC_API_KEY="..." # set it in the process environment, or the Secrets API; never write it into files you commit
Run it
Start it and prove it works.
uv run agent.py # the README's agent.py with your task
Check: the tool starts without errors and responds.
Persistence and access
Scripts and outputs live in /workspace on the computer; browser profiles persist with the computer.
Check: after the machine pauses and resumes, the tool starts again with its state intact.
Make it a product
One computer per customer workspace; a queue in front; results and screenshots stored per customer.
Limits and costs
Pin the version you tested and update deliberately; these tools change quickly.
Give the tool only the credentials it needs, as secrets, not baked into files.
Prototype: keep it to one machine at the default size, skip replicas and custom hostnames you do not need, and delete everything when you are done.
Acceptance checks
Browser Use runs on a MIOSA computer and answers a real task.
State survives a pause and resume.
Each customer has its own workspace and its own instance; nothing is shared between them.
Everything it created can be deleted with nothing left running.
What your choices added
- Build a product. a workspace per customer, per-customer metering and bill-to
- Agent suggests a name. proposes 3 product names and picks one; commands use <product-name>
- Model: Anthropic. your own provider key
- Prototype. one small machine, no extras, easy to delete
What you're building
an open-source library that lets an AI agent drive a real browser Modelled on Browser Use, by Browser Use.
You give the library a task and a model; it controls a Chromium browser (pages, clicks, forms, extraction) in a loop until the task is done.
Primitives you'll use: Computer · Sandbox
- An agent that drives a real browser
- Extracts structured data from pages
- Works with your choice of model
- Open source and embeddable
You install and run the real Browser Use on MIOSA. Read the official docs first: docs.browser-use.com. Every install command below comes from them; if the docs and this guide disagree, the docs win. Browser Use is open source Python library.
What you need on MIOSA
Each row is one thing to create before you start. The number matches the step that uses it.
- Organization and API key Scopes every call; a workspace key is all a worker needs.
miosa api-key create app-key --preset agentDocs - Computer A persistent Linux desktop for browser, mouse, and screenshot work.
miosa computer create app-desktopDocs - Sandbox The isolated Linux workspace the agent writes code and runs commands in.
miosa create app-box --template nextjs --waitDocs - A workspace per customer Isolates each customer’s machines, deployments, and data as they onboard.
miosa workspace create customer-1Docs - Branding and white-label Your name and slug on previews, deployments, and the desktop; customers never see MIOSA.
miosa orgDocs - Usage metering and bill-to Usage per customer, and which account pays for new machines.
miosa org billDocs
Architecture
How it runs on MIOSA
Where it runs -> a MIOSA computer (a persistent desktop with a browser)
State and files -> Scripts and outputs live in /workspace on the computer; browser profiles persist with the computer.
Model -> your own provider key, never a MIOSA platform key
Your customers -> one workspace each, isolated from each other
Auth and tenancy
Your organization is the platform; customers never get a MIOSA account, they sign into YOUR product. One workspace per customer, created as they onboard, isolates their machines, runs and data.
miosa workspace create browser-use-customer-1Tag every machine and run with the customer id in `metadata`, and never query across customers. Meter usage per customer with GET /api/v1/usage and set who pays with PUT /api/v1/bill-to (/docs/platform/usage-and-billing).
Install Browser Use
Run these inside the computer (its terminal), in order. The commands are from the official docs.
curl -LsSf https://astral.sh/uv/install.sh | shpython3 --version # Python >= 3.11 is requireduv init --python 3.12uv add browser-useCheck: the install finishes without errors; the next sections configure and start it.
Configure
Put your own model key in `.env` (the README example uses OPENAI_API_KEY). A MIOSA computer already has a desktop and Chrome for the agent to drive; use Browser Use's cloud browser only if you choose to.
Model: Anthropic (Claude). Calls use my own provider key (ANTHROPIC_API_KEY); MIOSA platform keys are never used.
export ANTHROPIC_API_KEY="..." # set it in the process environment, or the Secrets API; never write it into files you commitRun it
Start it and prove it works.
uv run agent.py # the README's agent.py with your taskCheck: the tool starts without errors and responds.
Persistence and access
Scripts and outputs live in /workspace on the computer; browser profiles persist with the computer.
Check: after the machine pauses and resumes, the tool starts again with its state intact.
Make it a product
One computer per customer workspace; a queue in front; results and screenshots stored per customer.
Limits and costs
Pin the version you tested and update deliberately; these tools change quickly.
Give the tool only the credentials it needs, as secrets, not baked into files.
Prototype: keep it to one machine at the default size, skip replicas and custom hostnames you do not need, and delete everything when you are done.
Acceptance checks
Browser Use runs on a MIOSA computer and answers a real task.
State survives a pause and resume.
Each customer has its own workspace and its own instance; nothing is shared between them.
Everything it created can be deleted with nothing left running.