Local-first routing
Connect local servers, Ollama-style endpoints, GGUF workflows, and API providers without forcing every prompt through one vendor account.
Local AI desktop app
A local AI desktop app that keeps model choice and context on your machine.
MultiAgentOS gives builders a private desktop workspace for local LLMs, API models, files, screenshots, voice, terminal commands, MCP servers, and user-defined tools.
Product demo
See the full desktop AI workspace.
Full-frame MultiAgentOS screenshots from the current app: a built-in browser the agent drives, the Bridge chat panel, model routing, and structured results together.
- 1 Ask
- 2 Route model
- 3 Run tools
- 4 Review action
Why local desktop AI matters
Cloud chatbots are useful, but many real workflows start on the desktop: files, folders, terminals, browser sessions, local services, screenshots, and apps. MultiAgentOS keeps those surfaces close to the user and lets the model route work through explicit connection types.
What it can connect to
- Local models through Ollama, local servers, or GGUF workflows.
- Cloud APIs such as OpenAI, Anthropic, DeepSeek, and compatible providers.
- MCP servers, terminal templates, command tools, scripts, files, folders, screenshots, and voice input.
Best fit
Use it when you want a durable desktop AI app instead of another browser tab: research, coding, documentation, file work, local model experimentation, and private agent tasks.
Local AI desktop app FAQ
Can I use cloud models too?
Yes. Local-first does not mean local-only. You can keep sensitive tasks on local models and route other work to API providers when needed.
Does this replace my IDE?
No. It complements your editor by adding a desktop-level AI surface with files, screenshots, commands, and tool access outside the IDE.
What to look for in a local AI desktop app
Local AI software should make privacy and model choice practical, not ceremonial. A useful local desktop app needs local model routing, clear cloud opt-in, file context, and a workflow surface that matches the way desktop work actually happens.
Desktop context
Use files, folders, screenshots, terminal commands, and browser/code/terminal sidecars as first-class context instead of treating the desktop as an afterthought.
Operational controls
Keep stop controls, visible status, connection settings, and review points in the same app frame so long tasks remain understandable.
Local-first does not mean weaker workflows
The best local AI desktop setup is hybrid by design. Run private or routine tasks on local models, route harder reasoning to a cloud provider when you choose, and keep the same file and tool context around both. MultiAgentOS is built for that mixed reality: six connection modes, sidecars for work surfaces, and supervised subagents for bounded delegation.
Good first workflows
- Summarize and reorganize a local notes folder without uploading it to a cloud workspace.
- Use an Ollama model for private drafts, then switch to a hosted model for final critique.
- Attach screenshots and files to debug a desktop problem with visible context.
- Use terminal or MCP tools for repeatable local tasks while keeping review controls visible.
Try a local-first AI desktop workflow.
Start with the product page, then use the guides to connect Ollama, OpenAI API keys, MCP tools, and desktop automation.
Questions
Frequently asked questions
Can MultiAgentOS run local models?
Yes. MultiAgentOS can connect to local model runtimes such as Ollama and local server endpoints, while still letting users route some work to API providers when they choose.
Is it only a chatbot?
No. It is a desktop AI workspace with files, screenshots, voice input, MCP servers, command tools, and controlled desktop actions.