Focused agents,running in parallel,with the plan in the open.
Work is decomposed and dispatched to specialized agents that run concurrently, with the plan visible as it executes. Build your own, chain them into workflows that run on a trigger, and reach any of it from the apps you already have open.
One plan, several agents, genuinely concurrent.
The planner dispatches independent work in parallel and only joins where a step actually depends on another's output.
A plan finishes as a screen, not a report.
Several agents ran, each against a different source, and what lands is one composed interface. Drawn here by the desktop's own renderer: the data is invented, everything else is the real thing.
What does my week actually look like?
Four things want you this week
Where the hours went
Uninterrupted blocks per day, Monday to Sunday.
Who does what.
Orchestrator
Decomposes intent into a plan and dispatches the rest.
Research
Gathers and cross-checks sources for long-form questions.
Browser
Drives a real browser session to reach what has no API.
Code
Plans and makes multi-file changes inside your workspace.
Analysis
Runs numerical work over the data the others returned.
Memory
Recalls prior context and workflows from the local vector store.
Shopping
Finds, compares and assembles options across retailers before you commit.
Yours
Agents you define yourself, with their own remit and tools.
It remembers, and the memory stays here.
A local vector store holds past contexts, workflows and preferences, so the operating system anticipates rather than re-asks. Because it is local, it can hold things you would never upload, and that is exactly what makes it useful.
- Recalls prior workflows, not just prior messages
- Indexes your documents on device, with no upload step
- Preferences are learned from what you accept and reject
- Clearing memory is a local delete, not a support request
- The plan, before it runs
- Tasks are broken out and streamed to you as a checklist, not summarised after the fact.
- Progress, as it happens
- Each step reports what it is doing, so a long job is legible rather than a spinner.
- Cancellation
- Long jobs can be stopped mid-flight without leaving the workspace half-changed.
- Which tools were used
- The tools an agent reached for are part of the trace, not hidden behind the answer.
Agents reach your tools through MCP.
The Model Context Protocol is how agents get at systems MeghaOS does not ship: your databases, internal APIs, ticketing, and anything else you already run.
The roster is a starting point, not a fixed list.
Describe an agent you need and it is written, registered, and available beside the built-in ones, running on your machine like the rest.
Describe the job, not the plumbing
Say what the agent should be responsible for and what it should be able to reach. The system writes it, registers it, and it appears alongside the built-in ones.
Give it a persona and a remit
A tone, a specialism, a set of tools it may use and a set it may not. Two agents doing similar work can be told to weigh things differently.
It is yours, and it stays here
Custom agents live on your machine like everything else. Nothing is uploaded to be reviewed, approved, or listed in someone’s marketplace.
Share it like a file
An agent you built is a definition you can copy to another machine or hand to a colleague. There is no publishing step and no account in the middle.
Chain them into something that runs without you.
A single request is one shape of work. The other is a repeatable sequence that runs on a trigger and tells you when it is finished.
Multi-step work, laid out as a graph
Chain steps together where each one feeds the next, and branch where the work genuinely diverges. The shape is explicit rather than buried in a prompt.
Runs on a trigger, not just a prompt
Kick a workflow off yourself, or let it run when the condition it watches for happens. The machine does not have to be watched to do the work.
Parallel where the work is parallel
Independent branches execute concurrently and rejoin only where a step actually needs another’s output.
Legible while it runs
You can see which step is active, which have finished, and where it stopped, so a long job is inspectable rather than a progress bar.
You do not have to be at the machine.
Message it from the apps you already have open, or by email, and the work still happens on your own hardware.
From the chat apps you already have open
Message the agent from your team chat or a personal messenger and get the answer back in the same thread, without opening the workspace at all.
By email
Send it something to deal with and read the reply in your inbox. Useful for work you want to start from a phone and review later.
It comes to you when it is done
Long-running jobs notify you where you are rather than requiring you to sit and watch a window.
The machine is still the one working
A message is a way to reach the agent. The reasoning, the files and the memory stay on your own hardware.
Run it on your own machine.
Free to download. Nothing leaves the device unless you connect it. Enterprise deployment is a conversation away.