How to Run Anthropic Computer Use Locally (2026 Guide)

What Is Anthropic Computer Use?

Anthropic Computer Use is a capability built into Claude that allows the AI to interact with a computer interface — viewing the screen, moving the cursor, clicking buttons, typing text, and navigating apps — exactly the way a human would. Instead of relying on pre-built integrations or custom APIs for every app, Claude can now control any software visually, using screenshots as its eyes.

This makes Claude a general-purpose desktop agent. Whether it's filling out a spreadsheet, opening a file manager, submitting a form in a web app, or running a terminal command — Claude can do it. No custom plugin required. No API endpoint needed. Just Claude, a screen, and a task.

For developers, the Computer Use capability is available through the Anthropic API with a Docker-based local demo. For everyday users, it ships as part of Claude Cowork and Claude Code on the macOS desktop app — making it accessible without a single line of code.

If you've been watching the rise of AI automation tools like OpenClaw and wondered when Anthropic would enter the game — that moment arrived on March 24, 2026.

Breaking: Claude Computer Use Goes Live — March 24, 2026

On March 24, 2026, Anthropic officially launched Computer Use as a research preview for Claude Pro and Max subscribers on macOS. The announcement marks a pivotal moment in the agentic AI race.

With this update, Claude gained the ability to open apps on your computer, navigate the web browser, fill in spreadsheets, and complete workflows from end to end — all triggered by a single natural language instruction. Anthropic even demonstrated a user running late for a meeting who asked Claude to export a pitch deck as a PDF and attach it to a calendar invite. Claude executed the entire task autonomously.

The feature pairs with Dispatch, Anthropic's mobile task-assignment tool released the previous week. With Dispatch, you can assign tasks to Claude directly from your iPhone. Claude then completes them on your desktop computer while you're away.

"Computer use is still early compared to Claude's ability to code or interact with text. Claude can make mistakes, and while we continue to improve our safeguards, threats are constantly evolving." — Anthropic

The capability is available inside Claude Cowork (for non-developers) and Claude Code (for developers), both within the macOS Claude Desktop application. Windows support is on the roadmap.

For developers who want more control or need to run Computer Use on Linux/Windows, the original Computer Use API with Docker — released in 2024 and continuously updated — remains the most powerful local option. Both methods are covered in full detail below.

How Claude Computer Use Works (Technical Overview)

Under the hood, Claude Computer Use operates as a continuous screenshot-analyze-act loop. Here is what happens at each step:

1. Screenshot Capture: Claude takes a screenshot of the current desktop or application screen at a recommended resolution of 1024×768 (XGA). Higher resolutions are downscaled to this size for optimal model accuracy.
2. Visual Analysis: Claude's multimodal vision model processes the screenshot — reading text, identifying UI buttons, understanding application context, and locating interactive elements.
3. Action Decision: Based on the task and what it sees, Claude decides on the next action: click a button, type text, scroll, open a new app, or run a command.
4. Action Execution: The action is passed to your application (or the Docker container) which physically executes it on the desktop.
5. Loop Repeat: Claude takes a new screenshot, assesses progress, and continues until the task is complete or the iteration limit is reached.

The API provides three core tool types for this loop:

• computer_20251124 — The primary computer interaction tool (screen control, click, type, scroll)
• str_replace_based_edit_tool — Text editor for reading and editing files
• bash_20250124 — Direct bash shell access for running commands

When using Claude Cowork (the no-code route), this entire loop is abstracted away. Claude intelligently decides whether to use a connector (like Gmail or Slack), fall back to browser automation, or resort to direct screen interaction — choosing the fastest and most reliable method for each task.

This architecture is fundamentally what makes Claude's Computer Use different from traditional RPA (Robotic Process Automation) tools. RPA relies on brittle selectors and hard-coded workflows. Claude navigates by sight and reasoning — adapting dynamically to any interface, even ones it has never seen before.

Interested in how Claude compares to other agentic coding tools? Check out our breakdown of Claude Code vs GitHub Copilot.

Two Ways to Run Claude Computer Use Locally

Depending on your skill level and use case, there are two primary methods to run Anthropic Computer Use locally in 2026:

Method 1: Claude Cowork (No-Code, macOS)

Best for non-developers and power users who want to automate tasks on their Mac without writing any code. Requires a Claude Pro or Max subscription. Works directly from the Claude Desktop app.

Method 2: Computer Use API via Docker (Developer Setup)

Best for developers who want to build custom agents, integrate Computer Use into their own applications, or run it on Linux/Windows. Requires an Anthropic API key and Docker installed. Provides the full programmatic interface.

Both methods are covered below with complete step-by-step instructions.

Method 1: Claude Cowork — No-Code Desktop Agent Setup

Prerequisites

• macOS device (Windows support coming soon)
• Claude Pro ($20/mo) or Claude Max ($100–200/mo) subscription
• Latest version of the Claude Desktop app

Step 1: Download or Update Claude Desktop

Visit claude.com/download and install or update the Claude Desktop application. Make sure you are running the latest version — the Computer Use feature requires it.

Step 2: Enable Computer Use in Settings

1. Open the Claude Desktop app on your Mac.
2. Go to Settings → General (under the Desktop app section).
3. Find the Computer Use toggle and switch it on.

Step 3: Open Cowork Mode

Click Cowork in the sidebar or top tab area (next to Chat). This switches Claude from conversational mode into its task-execution agent mode.

Step 4: Grant App Permissions

When you assign Claude its first computer-use task, it will prompt you to grant permission for each app it needs to access. Review each prompt carefully and only approve apps you trust. Claude will never silently access an app without explicit permission.

By default, certain sensitive app categories — such as investment platforms and cryptocurrency wallets — are blocked and cannot be granted access.

Step 5: Assign Your First Task

Type a natural language instruction such as:

• "Open my Downloads folder, find all PDF files from this month, and move them into a folder called Reports."
• "Go to my Google Calendar and block two hours every morning next week for deep work."
• "Fill in the timesheet in the HR portal with this week's hours."

Claude will follow the instruction step-by-step, taking screenshots, clicking through your apps, and completing the task — with you able to observe every action in real time and stop it at any point.

Using Dispatch (Mobile Task Assignment)

With Anthropic's Dispatch feature, you can assign tasks to Claude from your iPhone and return to completed work on your Mac. Install the Claude mobile app, open Dispatch, and send a task message. Claude picks it up on your desktop and works through it while you're away — your computer just needs to stay awake.

Want to build more powerful automation workflows? Also explore how OpenClaw handles WhatsApp-based task automation for a complementary approach.

Method 2: Computer Use API via Docker (Developer Setup)

For developers who want full control — or need to run Computer Use on Windows or Linux — the Anthropic Computer Use API with a Docker-based demo environment is the way to go. This approach runs Claude inside an isolated container, giving it a sandboxed virtual desktop to interact with safely.

Prerequisites

• Docker Desktop installed on macOS, Windows, or Linux
• Anthropic API key — get one from console.anthropic.com
• Basic terminal knowledge
• At least 4GB free RAM recommended

Why Docker?

Running Computer Use inside Docker provides critical security isolation. Claude operates on a virtual desktop inside the container — not your real machine. This means it cannot accidentally delete files, access personal data, or interact with sensitive apps on your host system. For any production or experimentation use, Docker is the recommended and safest approach.

Thinking about running AI agents on a VPS or cloud server instead? See our guide on running AI agents on a VPS.

Full Docker Setup — Step-by-Step Commands

Step 1: Create the Anthropic Config Directory

mkdir -p $HOME/.anthropic

The -p flag ensures no error if the directory already exists.

Step 2: Export Your API Key

export ANTHROPIC_API_KEY=your_api_key_here

Replace your_api_key_here with your actual key from the Anthropic console. On Windows (PowerShell), use:

$env:ANTHROPIC_API_KEY = "your_api_key_here"

Step 3: Pull and Run the Docker Container

Run the following command to pull the latest Computer Use demo image and start the container:

docker run \
  -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
  -v $HOME/.anthropic:/home/computeruse/.anthropic \
  -p 5900:5900 \
  -p 8501:8501 \
  -p 6080:6080 \
  -p 8080:8080 \
  -it ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

What each port does:

• 8080 — Main web interface (the one you'll use in your browser)
• 6080 — noVNC web-based desktop viewer
• 5900 — VNC server (for external VNC clients)
• 8501 — Streamlit agent interface

Step 4: Run in Background (Optional)

To run the container detached (in the background), replace -it with -d:

docker run -d \
  -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
  -v $HOME/.anthropic:/home/computeruse/.anthropic \
  -p 5900:5900 \
  -p 8501:8501 \
  -p 6080:6080 \
  -p 8080:8080 \
  ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

Step 5: Set Custom Resolution (Optional)

For optimal model performance, Anthropic recommends using XGA resolution (1024×768). To explicitly set this:

docker run \
  -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
  -v $HOME/.anthropic:/home/computeruse/.anthropic \
  -p 5900:5900 -p 8501:8501 -p 6080:6080 -p 8080:8080 \
  -e WIDTH=1024 \
  -e HEIGHT=768 \
  -it ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

Higher resolutions will cause the image to be automatically downscaled, which can reduce model accuracy and speed. Stick to 1024×768 for best results.

Step 6: Access the Demo Interface

Once the container is running and you see "Computer Use Demo is ready!" in the terminal, open your browser and navigate to:

http://localhost:8080

This opens the combined web interface where you can chat with Claude, observe the virtual desktop, and watch Claude navigate and complete tasks in real time.

Step 7: Build the Image Locally (Advanced)

If you want to modify the demo or build from source:

git clone https://github.com/anthropics/anthropic-quickstarts.git
cd anthropic-quickstarts/computer-use-demo
docker build . -t computer-use-demo:local

Then run with computer-use-demo:local instead of the hosted image tag.

Windows-Specific Setup

On Windows, use this modified command in PowerShell or CMD:

SET ANTHROPIC_API_KEY=your_api_key_here
docker run -e ANTHROPIC_API_KEY=%ANTHROPIC_API_KEY% -v c:/tmp/.anthropic:/home/computeruse/.anthropic -p 5900:5900 -p 8501:8501 -p 6080:6080 -p 8080:8080 -it ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

Using AWS Bedrock or Google Vertex as Backend

If you prefer to use AWS or Google Cloud instead of the direct Anthropic API:

AWS Bedrock:

docker run \
  -e API_PROVIDER=bedrock \
  -e AWS_PROFILE=$AWS_PROFILE \
  -e AWS_REGION=us-west-2 \
  -v $HOME/.aws/credentials:/home/computeruse/.aws/credentials \
  -v $HOME/.anthropic:/home/computeruse/.anthropic \
  -p 5900:5900 -p 8501:8501 -p 6080:6080 -p 8080:8080 \
  -it ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

Google Vertex AI:

docker run \
  -e API_PROVIDER=vertex \
  -e CLOUD_ML_REGION=$VERTEX_REGION \
  -e ANTHROPIC_VERTEX_PROJECT_ID=$VERTEX_PROJECT_ID \
  -v $HOME/.config/gcloud/application_default_credentials.json:/home/computeruse/.config/gcloud/application_default_credentials.json \
  -p 5900:5900 -p 8501:8501 -p 6080:6080 -p 8080:8080 \
  -it ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

For a deeper look at how to pair AI APIs with custom local models, see our guide on building a local AI agent with Python, Ollama, and LangChain.

Understanding the Agent Loop (Developer Deep Dive)

The core of the Computer Use API is an agent loop — a cycle where Claude requests a tool action, your application executes it, and returns the result back to Claude. Here is a simplified Python implementation of the loop:

async def sampling_loop(
    *,
    model: str,
    messages: list[dict],
    api_key: str,
    max_tokens: int = 4096,
    tool_version: str,
    thinking_budget: int | None = None,
    max_iterations: int = 10,  # Prevents infinite loops
):
    """
    A simple agent loop for Claude computer use interactions.
    """
    client = anthropic.Anthropic(api_key=api_key)
 
    for _ in range(max_iterations):
        response = client.beta.messages.create(
            model=model,
            max_tokens=max_tokens,
            messages=messages,
            tools=[
                {
                    "type": "computer_20251124",
                    "name": "computer",
                    "display_width_px": 1024,
                    "display_height_px": 768,
                    "display_number": 1
                },
                {
                    "type": "text_editor_20250728",
                    "name": "str_replace_based_edit_tool"
                },
                {
                    "type": "bash_20250124",
                    "name": "bash"
                }
            ],
            betas=["computer-use-2025-11-24"],
        )
 
        # Check if task is complete
        if response.stop_reason == "end_turn":
            break
 
        # Execute Claude's requested tool actions
        tool_results = execute_tool_calls(response.content)
 
        # Feed results back to Claude for next iteration
        messages += [
            {"role": "assistant", "content": response.content},
            {"role": "user", "content": tool_results}
        ]
 
    return messages

The max_iterations parameter is important — without it, a complex task could cause Claude to loop indefinitely. Always set a sensible upper bound. For simple tasks, 10 iterations is sufficient. Complex workflows may need 25–50.

Note that the Computer Use beta adds approximately 466–499 tokens to the system prompt as overhead. Factor this into your token cost calculations for production workloads.

For developers exploring AI API integrations further, see our guide to using OpenRouter API with Next.js.

Real-World Use Cases for Computer Use Locally

Here are some of the most practical and impactful ways developers and power users are running Anthropic Computer Use locally right now:

Developer Productivity

• Open an IDE, make code changes across multiple files, run tests, and submit a pull request — all from a single prompt
• Navigate an internal dashboard that has no public API and extract data into a spreadsheet
• Set up a local dev environment from scratch following a README file

Office and Document Automation

• Fill a spreadsheet with data from multiple websites and local files, then format and save it to a shared folder
• Export a presentation as PDF and attach it to a calendar invite before a meeting
• Batch rename and reorganize files across multiple directories

Research and Data Collection

• Browse multiple websites, collect comparative data, and compile it into a formatted analysis report
• Navigate an internal HR tool to pull last quarter's reports and summarize them

QA and App Testing

• Open a mobile phone simulator, interact with an app you're developing, and identify UX issues
• Run through a browser-based test checklist and log results automatically

Career and Job Search Workflows

Job seekers can use computer-use style AI agents to automate repetitive application steps. While practicing your interview skills, tools like Cloudvyn's AI interview platform can complement agentic workflows — helping you not just apply for jobs faster, but prepare better for the interviews that follow.

Claude Computer Use vs OpenClaw: Key Differences

OpenClaw is the open-source AI agent that went viral earlier in 2026, sparking the current wave of computer-use AI agents. Claude's Computer Use is often described as "Anthropic's version of OpenClaw." Here is how they compare:

For a more detailed comparison of these agentic tools, see our full writeup on OpenClaw vs n8n for AI automation.

Safety Best Practices When Running Computer Use Locally

Computer Use is powerful — and with that power comes real responsibility. Whether you're using Claude Cowork or the Docker-based API, follow these safety guidelines to protect your data and your system.

For Cowork Users

• Only grant access to apps you trust. Claude will prompt before accessing each application — review each request before approving.
• Close sensitive apps before starting a session. Claude takes screenshots of whatever is visible, so close your banking app, password manager, or any document with private information.
• Add sensitive apps to the blocklist. In Settings, you can prevent Claude from ever accessing specific applications, even accidentally.
• Start with simple, reversible tasks. Don't begin by asking Claude to reorganize your entire file system. Start with research, formatting, or low-stakes data tasks.
• Never use Computer Use for financial transactions, medical data, or legal documents. Anthropic explicitly advises against this.

For Docker API Users

• Always run inside the Docker container. This sandboxes Claude away from your real file system, preventing accidental modifications to important files.
• Do not mount sensitive directories. Only mount the ~/.anthropic config directory. Never mount your home folder or any directory containing personal data.
• Set an iteration limit in your agent loop. Use the max_iterations parameter to prevent runaway loops that waste API credits or cause unintended actions.
• Review Claude's action logs. The Docker demo UI shows a full action-by-action log. Review it during development to catch unexpected behavior.
• Watch for prompt injection. Anthropic has built classifiers to detect prompt injection attacks — where malicious content on a webpage tries to hijack Claude's instructions. But no safeguard is perfect. Monitor Claude when it browses untrusted websites.

General Guidelines

• Claude is trained to avoid stock trading, investment transactions, and scraping facial images — but these are trained guardrails, not hard technical blocks.
• Anthropic's computer use memory system excludes passwords, financial details, and health information from persistent memory. But treat any screen with sensitive data as potentially visible.
• When in doubt, stop the task using the in-app stop button or by terminating the Docker container.

Current Limitations to Know in 2026

Anthropic is transparent that Computer Use is still an early-stage capability. Here are the known limitations as of March 2026:

• macOS only for Cowork/Claude Code. The native desktop computer use features work only on macOS. Windows support has been announced but not yet released.
• Slower than direct integrations. When Claude navigates your screen instead of using a built-in connector (like Gmail or Google Drive), tasks take significantly longer. Use connectors wherever possible.
• Complex multi-step tasks may need retries. The AI can make mistakes in long workflows, particularly when UI layouts change or network delays introduce unexpected screen states.
• Screenshot-based overhead adds cost. Each screenshot requires vision processing tokens. For the API route, a simple task can cost around $0.30 USD and take 1–2 minutes. Factor this into production cost planning.
• One session at a time. The Docker demo agent loop supports only one active session. Restart the container between sessions for a clean state.
• Pro or Max plan required for Cowork. Free plan users do not have access to the Computer Use feature via Cowork or Claude Code.

Despite these limitations, the trajectory is clear — Computer Use will rapidly improve. The research preview model improves based on user feedback, and Anthropic has made this explicit in their communications.

Frequently Asked Questions

Can I run Anthropic Computer Use locally without a paid plan?

The Claude Cowork and Claude Code computer use features require a Claude Pro or Max subscription. However, developers can access the Computer Use API through Anthropic's API with pay-per-use credits and run the Docker-based demo locally without a monthly subscription. You only pay for the tokens you use.

Does Anthropic Computer Use work on Windows and Linux?

The Claude Cowork and Claude Code desktop features currently support macOS only, with Windows support on the roadmap. The Docker-based Computer Use API demo, however, runs on macOS, Windows, and Linux via Docker Desktop.

What is the difference between Claude Cowork computer use and the Computer Use API?

Claude Cowork is a ready-to-use desktop agent for everyday users who want to automate tasks without writing code. The Computer Use API is for developers building custom automation workflows, agents, and applications. The API gives full programmatic control via Docker and Python.

Is Claude Computer Use safe to run locally?

When using the Docker API route, Claude runs inside an isolated container — not your real machine — which is the safest approach for experimentation. For Cowork, Claude only accesses apps you explicitly approve, and Anthropic includes trained safeguards against harmful actions. That said, no safeguard is absolute. Always follow the safety best practices outlined in this guide.

How much does the Computer Use API cost per task?

Costs vary by task complexity. A simple web browsing task (searching and retrieving information) can cost around $0.20–$0.50 USD due to repeated screenshot processing and token consumption. Computer use follows standard Anthropic API pricing — check the Anthropic console for the latest token rates per model.

Can Claude Computer Use help with job applications?

Yes — Claude can navigate job portals, fill in application forms, and organize your job search workflow. But what happens after you apply? That's where AI interview preparation platforms come in. Use Cloudvyn to practice mock interviews and get AI feedback before your actual screening.

Can I integrate Computer Use with my existing AI automation setup?

Yes. The Computer Use API can be integrated into larger agentic workflows using Python. You can combine it with LangChain, local LLMs via Ollama, or other orchestration tools. See our guide on building local AI agents with Python and Ollama for a foundational setup.

Conclusion

Anthropic's Computer Use capability represents one of the most significant leaps in practical AI utility in 2026. Whether you're an everyday professional wanting to offload repetitive computer tasks to Claude via Cowork, or a developer building custom desktop automation agents through the Docker API — the tools are available right now.

The March 24, 2026 research preview launch confirms that agentic AI has moved from concept to production-ready reality. Claude can open your apps, navigate your browser, fill in forms, run dev tools, and complete complex multi-step workflows — all from a single natural language instruction.

Here is a quick summary of what you've learned in this guide:

• What Anthropic Computer Use is and how the screenshot-analyze-act loop works
• Two ways to run it locally: Claude Cowork (no-code, macOS) and the Computer Use API (Docker, any OS)
• Full Docker setup commands including API key configuration, port mappings, and resolution settings
• The agent loop code for Python developers
• How it compares to OpenClaw and when to use each
• Safety best practices to protect your data and system
• Current limitations to set realistic expectations

If you found this guide helpful, explore the rest of the Cloudvyn blog for more deep-dives on AI agents, developer tools, and career tech:

• Setting up Claude Code with OpenClaw
• Installing the OpenClaw browser extension
• Claude Code vs GitHub Copilot: Which wins in 2026?
• Integrating OpenRouter API with Next.js
• Best AI Interview Platforms of 2026

And if you're a job seeker in India preparing for your next technical interview, check out Cloudvyn's AI mock interview platform — practice with real-time AI feedback, voice interviews in Hindi and English, and get your resume analyzed for free.