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Ollama GUI for agents

Use Ollama models from a desktop agent interface.

MultiAgentOS adds an agent-friendly GUI around local Ollama models: files, screenshots, tools, model routing, reusable prompts, and desktop actions.

Ollama setup guideCompare Open WebUI
Connection modes

Route each task through the right model or tool surface.

MultiAgentOS supports API keys, local servers, CLI pipes, OAuth, terminal templates, and local AI/GGUF workflows, so you can use a cheaper provider or a fully private local model.

  1. 1 Choose provider
  2. 2 Store secret
  3. 3 Test model
  4. 4 Enable tools
Full-frame MultiAgentOS settings showing the LLM provider picker with many providers.
Full-frame screenshot from the current MultiAgentOS app.
API key screenshot in MultiAgentOS.
API key Bring your own key for OpenAI, Anthropic, DeepSeek, Groq, and 30+ other providers.
Local server screenshot in MultiAgentOS.
Local server Point MultiAgentOS at Ollama, LM Studio, or any OpenAI-compatible local endpoint.
MCP connect screenshot in MultiAgentOS.
MCP connect Add external tools and data sources over the Model Context Protocol.

Local inference

Keep private prompts on local models when the task can be handled on your machine.

Agent context

Add files, folders, screenshots, voice input, and command surfaces around the model.

Hybrid routing

Use Ollama for private work and switch to API providers when a task needs a stronger hosted model.

Why not just use a basic local model chat UI?

Basic local chat is great for prompts. Agent work needs durable connections, tool loading, file context, computer actions, and routing across models. MultiAgentOS is built to put those pieces in one desktop surface.

Recommended path

  1. Install Ollama and pull a tool-capable model.
  2. Connect the local server in MultiAgentOS.
  3. Add file and screenshot context for the task.
  4. Enable the tools or MCP servers the workflow needs.

Ollama GUI features that matter for agents

An agent-oriented Ollama GUI should do more than send messages to `localhost:11434`. It should help the user decide when to stay local, when to route to a hosted model, and what tools the model is allowed to use.

Connection testing

Confirm the local server, selected model, and route before the task starts so failures do not happen halfway through a workflow.

File and screenshot context

Give the local model the context it needs without pasting huge prompts by hand or copying files into a separate web app.

Tool boundaries

Expose command tools, MCP servers, and sidecars only when the task requires them, then keep the result visible for review.

Ollama agent workflow examples

WorkflowLocal model roleMultiAgentOS role
Private note cleanupSummarize and classify local text.Attach folders, preserve context, and return reviewable output.
Codebase orientationExplain files and propose small edits.Open code sidecar, terminal sidecar, and supervised review controls.
Desktop troubleshootingReason over screenshots and logs.Keep screenshots, commands, and the active prompt route in one frame.

Questions

Frequently asked questions

Does MultiAgentOS replace Ollama?

No. Ollama runs the local models. MultiAgentOS provides the desktop interface, routing, context, tools, and agent workflow layer around it.

Can I still use API models?

Yes. You can combine Ollama with API providers and choose the right model per task.