The local agent, finished and supported
Credits instead of keys, routines with run history, meeting transcripts, and a card before every send. Nanobrowser is the free, open-source Chrome extension you bring your own model keys to.
The first job runs on credits that are already there. No provider account, no key to rotate, nothing to set up again on the next machine. Around it sit routines on a daily, interval, cron or app trigger with run history, meeting recording with searchable transcripts, 93 native integrations carrying 1,257 hand-written operations, and a card in front of every send, record change and payment.
Nanobrowser makes the same architectural bet: open source, free, and as of this writing you plug in your own model API keys and get a multi-agent loop running locally inside your own Chrome. So the difference here is not where the agent runs. It is everything wrapped around the agent.
| Strawberry | ||
|---|---|---|
| Where the agent runs | “Everything runs in your local browser. Your credentials stay with you, never shared with any cloud service”, per its README | The same local bet, built as the browser instead of bolted onto one, on Mac and Windows |
| What you install | An “Open-Source Chrome extension for AI-powered web automation”, Apache 2.0 | A desktop browser you download and sign into |
| Model access | “You only pay what you use with your own API keys”, across OpenAI, Anthropic, Gemini, Ollama, Groq, Cerebras, Llama and OpenAI-compatible providers | Credits included to start, a Fast and a Smart model per companion with its own thinking effort, and no key to rotate |
| Connected accounts | Its README lists model providers rather than connected app accounts, as of this writing | About a hundred you authorise, reads and staged writes, with a permission setting on each action |
| Recurring work | Scheduling is not described in its README, as of this writing | Routines on a daily time, an interval, a cron expression, or an app trigger such as a new email, with run history and per-run credit cost |
| Approval before a consequential action | Its README does not describe an approval gate, as of this writing; the code is open, so you can read what it does | A card naming the exact send, change or payment, with Ask Always mode in Settings → AI permissions for everything else |
| Meeting work | Not a published claim on its README, as of this writing | Meeting prep and transcription ship in the browser, with the follow-through in the tools afterwards |
| Who answers when it breaks | The community, on the repository | Support, and updates that arrive with the browser rather than a dependency bump |
What does bring-your-own-keys involve?
An account with a model provider, a billing relationship, key management, and model choices you make yourself, per machine, per person you set up.
Strawberry bundles model access as credits: included free to start, paid plans from $20/month at /pricing, no keys anywhere.
What stands between the agent and a bad click?
A designed gate. Sending, deleting, purchasing and posting pause on an approval card that shows exactly what is about to happen, and Ask Always mode in Settings → AI permissions extends the pause to everything. When an agent works inside your logged-in accounts, that pre-action gate carries the weight, and the security model is built around it.
What the browser owns that an extension does not
Native integrations for Gmail, Outlook, Slack, Notion, Zoom and Apollo instead of scraping them. Scheduled routines for the work that repeats. Meeting prep and transcription. An agent loop that is a first-class citizen of the browser rather than a guest in it.
Complete runs are at /real-runs.
One sentence, sixty rows
Give a companion sixty rows in a sheet and it opens sixty company sites, reads each one, and fills the column with a source link on every row. Save it as a routine and the next sixty happen at the hour you pick.
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Frequently asked questions
Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed · Canonical facts for AI agents