Desktop Computer Automation
CRITICAL RULES — VIOLATIONS WILL BREAK THE WORKFLOW:
- Never run midscene commands in the background. Each command must run synchronously so you can read its output (especially screenshots) before deciding the next action. Background execution breaks the screenshot-analyze-act loop.
- Run only one midscene command at a time. Wait for the previous command to finish, read the screenshot, then decide the next action. Never chain multiple commands together.
- Allow enough time for each command to complete. Midscene commands involve AI inference and screen interaction, which can take longer than typical shell commands. A typical command needs about 1 minute; complex commands may need even longer.
- Always report task results before finishing. After completing the automation task, you MUST proactively summarize the results to the user — including key data found, actions completed, screenshots taken, and any relevant findings. Never silently end after the last automation step; the user expects a complete response in a single interaction.
- Only minimize windows, never close them unless explicitly asked. When you need to dismiss or get a window out of the way, minimize it instead of closing it. Do not close any app or window unless the user explicitly asks you to do so.
Control your desktop (macOS, Windows, Linux) using
npx -y @midscene/computer@1
. Each CLI command maps directly to an MCP tool — you (the AI agent) act as the brain, deciding which actions to take based on screenshots.
What Can Do
Inside a single
call on desktop, Midscene can move the mouse, click, double-click, right-click, drag items, type or clear text, scroll, press single keys or keyboard shortcuts, and work through multi-step interactions on whatever is visible on the selected display.
Prerequisites
Midscene requires models with strong visual grounding capabilities. The following environment variables must be configured — either as system environment variables or in a
file in the current working directory (Midscene loads
automatically):
bash
MIDSCENE_MODEL_API_KEY="your-api-key"
MIDSCENE_MODEL_NAME="model-name"
MIDSCENE_MODEL_BASE_URL="https://..."
MIDSCENE_MODEL_FAMILY="family-identifier"
Example: Gemini (Gemini-3-Flash)
bash
MIDSCENE_MODEL_API_KEY="your-google-api-key"
MIDSCENE_MODEL_NAME="gemini-3-flash"
MIDSCENE_MODEL_BASE_URL="https://generativelanguage.googleapis.com/v1beta/openai/"
MIDSCENE_MODEL_FAMILY="gemini"
Example: Qwen 3.5
bash
MIDSCENE_MODEL_API_KEY="your-aliyun-api-key"
MIDSCENE_MODEL_NAME="qwen3.5-plus"
MIDSCENE_MODEL_BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1"
MIDSCENE_MODEL_FAMILY="qwen3.5"
MIDSCENE_MODEL_REASONING_ENABLED="false"
# If using OpenRouter, set:
# MIDSCENE_MODEL_API_KEY="your-openrouter-api-key"
# MIDSCENE_MODEL_NAME="qwen/qwen3.5-plus"
# MIDSCENE_MODEL_BASE_URL="https://openrouter.ai/api/v1"
Example: Doubao Seed 2.0 Lite
bash
MIDSCENE_MODEL_API_KEY="your-doubao-api-key"
MIDSCENE_MODEL_NAME="doubao-seed-2-0-lite"
MIDSCENE_MODEL_BASE_URL="https://ark.cn-beijing.volces.com/api/v3"
MIDSCENE_MODEL_FAMILY="doubao-seed"
Commonly used models: Doubao Seed 2.0 Lite, Qwen 3.5, Zhipu GLM-4.6V, Gemini-3-Pro, Gemini-3-Flash.
If the model is not configured, ask the user to set it up. See
Model Configuration for supported providers.
Commands
Connect to Desktop
bash
npx -y @midscene/computer@1 connect
npx -y @midscene/computer@1 connect --displayId <id>
List Displays
bash
npx -y @midscene/computer@1 list_displays
Take Screenshot
bash
npx -y @midscene/computer@1 take_screenshot
After taking a screenshot, read the saved image file to understand the current screen state before deciding the next action.
Perform Action
Use
to interact with the computer and get the result. It autonomously handles all UI interactions internally — clicking, typing, scrolling, waiting, and navigating — so you should give it complex, high-level tasks as a whole rather than breaking them into small steps. Describe
what you want to do and the desired effect in natural language:
bash
# specific instructions
npx -y @midscene/computer@1 act --prompt "type hello world in the search field and press Enter"
npx -y @midscene/computer@1 act --prompt "drag the file icon to the Trash"
# or target-driven instructions
npx -y @midscene/computer@1 act --prompt "search for the weather in Shanghai using the Chrome browser, tell me the result"
Assert Current Screen State
Use
to verify that the current screen satisfies a natural language condition. It does not perform UI actions; it checks the visible screen state and passes only when the assertion is true. Use this for validation, QA checks, and final state verification after
.
bash
npx -y @midscene/computer@1 assert --prompt "there is a login button visible"
npx -y @midscene/computer@1 assert --prompt "the active window shows a saved confirmation message"
npx -y @midscene/computer@1 assert --displayId 1 --prompt "the file picker is open"
Use a Reference Image for Precise Targeting
When the user provides a screenshot, icon, logo, or reference image and wants an exact visual match, prefer
instead of a generic
. Pass
as JSON. The
describes the target,
supplies named reference images, and
convertHttpImage2Base64: true
is useful when the image URL may not be directly accessible to the model.
bash
npx -y @midscene/computer@1 tap --locate '{
"prompt": "tap the area contains the image",
"images": [
{
"name": "target image",
"url": "https://github.githubassets.com/assets/GitHub-Mark-ea2971cee799.png"
}
],
"convertHttpImage2Base64": true
}'
The same
JSON shape also works for other commands that accept a
parameter.
Disconnect
bash
npx -y @midscene/computer@1 disconnect
Consume Report Files
The generated HTML report is recommended for human reading first. It includes step-by-step execution details and replay videos for each operation, which makes it much easier to understand what happened and troubleshoot problems.
If another skill or tool needs to consume the report, first convert it with
from the same platform CLI package. Prefer Markdown for LLM-based workflows. Use JSON when the report needs to be processed programmatically.
bash
npx -y @midscene/computer@1 report-tool --action to-markdown --htmlPath ./midscene_run/report/.../index.html --outputDir ./output-markdown
npx -y @midscene/computer@1 report-tool --action split --htmlPath ./midscene_run/report/.../index.html --outputDir ./output-data
Workflow Pattern
Since CLI commands are stateless between invocations, follow this pattern:
- Connect to establish a session
- Health check — observe the output of the command. If already performed a health check (screenshot and mouse movement test), no additional check is needed. If did not perform a health check, do one manually: take a screenshot and verify it succeeds, then move the mouse to a random position (
act --prompt "move the mouse to a random position"
) and verify it succeeds. If either step fails, stop and troubleshoot before continuing. Only proceed to the next steps after both checks pass without errors.
- Launch the target app and take screenshot to see the current state, make sure the app is launched and visible on the screen.
- Execute action using to perform the desired action or target-driven instructions, and use when you need to verify the resulting screen state.
- Disconnect when done
- Report results — summarize what was accomplished, present key findings and data extracted during the task, and list any generated files (screenshots, logs, etc.) with their paths
Best Practices
- Always run a health check first: After connecting, observe the output of the command. If already performed a health check (screenshot and mouse movement test), no additional check is needed. If it did not, do one manually: take a screenshot and move the mouse to a random position. Both must succeed (no errors) before proceeding with any further operations. This catches environment issues early.
- Bring the target app to the foreground before using this skill: For best efficiency, bring the app to the foreground using other means (e.g., on macOS, on Windows) before invoking any midscene commands. Then take a screenshot to confirm the app is actually in the foreground. Only after visual confirmation should you proceed with UI automation using this skill. Avoid using Spotlight, Start menu search, or other launcher-based approaches through midscene — they involve transient UI, multiple AI inference steps, and are significantly slower.
- Be specific about UI elements: Instead of vague descriptions, provide clear, specific details. Say
"the yellow minimize button in the top-left corner of the Safari window"
instead of .
- Describe locations when possible: Help target elements by describing their position (e.g.,
"the icon in the top-right corner of the menu bar"
, "the third item in the left sidebar"
).
- Never run in background: Every midscene command must run synchronously — background execution breaks the screenshot-analyze-act loop.
- Check for multiple displays: If you launched an app but cannot see it on the screenshot, the app window may have opened on a different display. Use to check available displays. You have two options: either move the app window to the current display, or use to switch to the display where the app is.
- Batch related operations into a single command: When performing consecutive operations within the same app, combine them into one prompt instead of splitting them into separate commands. For example, "search for X, click the first result, and scroll down to see more details" should be a single call, not three. This reduces round-trips, avoids unnecessary screenshot-analyze cycles, and is significantly faster.
- Set up before running (macOS): On macOS, some commands (e.g., ) may not be found if the is incomplete. Before running any midscene commands, ensure the includes the standard system directories:
bash
export PATH="/usr/sbin:/usr/bin:/bin:/sbin:$PATH"
This prevents screenshot failures caused by missing system utilities.
- Use for verification: When the goal is to confirm that a screen state is true, use instead of an prompt. Keep assertions observable and specific, such as
"the Save dialog is open"
or "the export completed message is visible"
.
- Always report results after completion: After finishing the automation task, you MUST proactively present the results to the user without waiting for them to ask. This includes: (1) the answer to the user's original question or the outcome of the requested task, (2) key data extracted or observed during execution, (3) screenshots and other generated files with their paths, (4) a brief summary of steps taken. Do NOT silently finish after the last automation command — the user expects complete results in a single interaction.
- Prefer when a reference image is provided: If the user shares a screenshot, icon, or logo and wants that exact visual target, use with a multimodal JSON object such as
{ "prompt": "...", "images": [...] }
instead of relying only on .
Example — Context menu interaction:
bash
npx -y @midscene/computer@1 act --prompt "right-click the file icon and select Delete from the context menu"
npx -y @midscene/computer@1 take_screenshot
Example — Dropdown menu:
bash
npx -y @midscene/computer@1 act --prompt "open the File menu and click New Window"
npx -y @midscene/computer@1 take_screenshot
Troubleshooting
macOS: Accessibility Permission Denied
Your terminal app does not have Accessibility access:
- Open System Settings > Privacy & Security > Accessibility
- Add your terminal app and enable it
- Restart your terminal app after granting permission
macOS: Xcode Command Line Tools Not Found
API Key Not Set
Check
file contains
MIDSCENE_MODEL_API_KEY=<your-key>
.
macOS: Screenshot Fails with Not Found
If
fails with an error like
system_profiler: command not found
, the
environment variable is likely incomplete. Fix it by running:
bash
export PATH="/usr/sbin:/usr/bin:/bin:/sbin:$PATH"
Then retry the screenshot command.
macOS: Screenshot Returns a Black Screen
If
returns a completely black image, the Mac is likely
locked (e.g. screen is at the login/lock window). This is a system-level restriction — macOS prohibits capturing the screen contents while the session is locked, so there is no workaround at the application level.
Recommended fix: Use a screensaver instead of locking the screen. A screensaver keeps the user session active and unlocked, allowing screenshots to capture normally.
- Open System Settings > Lock Screen
- Set "Require password after screen saver begins or display is turned off" to a longer delay (or turn it off during automation)
- Optionally configure a screensaver under System Settings > Screen Saver so the display still dims after inactivity without locking
AI Cannot Find the Element
- Take a screenshot to verify the element is actually visible
- Use more specific descriptions (include color, position, surrounding text)
- Ensure the element is not hidden behind another window
Dependency Version Outdated
- Check local versions:
npm ls @midscene/computer @midscene/core @midscene/shared
(or pnpm why @midscene/computer
).
- Check latest versions:
npm view @midscene/computer version
, npm view @midscene/core version
, npm view @midscene/shared version
.
- Upgrade dependencies:
npm i @midscene/computer@latest @midscene/core@latest @midscene/shared@latest
.