Install
openclaw skills install cursor-agentA comprehensive skill for using the Cursor CLI agent for various software engineering tasks (updated for 2026 features, includes tmux automation guide).
openclaw skills install cursor-agentThis skill provides a comprehensive guide and set of workflows for utilizing the Cursor CLI tool, including all features from the January 2026 update.
curl https://cursor.com/install -fsS | bash
brew install --cask cursor-cli
macOS:
~/.zshrc (zsh) or ~/.bashrc (bash):
export PATH="$HOME/.local/bin:$PATH"
source ~/.zshrc (or ~/.bashrc)Linux/Ubuntu:
agent --versionBoth platforms:
agent (primary) and cursor-agent (backward compatible)agent --version or cursor-agent --versionAuthenticate via browser:
agent login
Or use API key:
export CURSOR_API_KEY=your_api_key_here
Keep your CLI up to date:
agent update
# or
agent upgrade
Start an interactive session with the agent:
agent
Start with an initial prompt:
agent "Add error handling to this API"
Backward compatibility: cursor-agent still works but agent is now the primary command.
List all available models:
agent models
# or
agent --list-models
Use a specific model:
agent --model gpt-5
Switch models during a session:
/models
Manage your agent sessions:
agent lsagent resumeagent --resume="[chat-id]"Include specific files or folders in the conversation:
@filename.ts
@src/components/
Available during interactive sessions:
/models - Switch between AI models interactively/compress - Summarize conversation and free up context window/rules - Create and edit rules directly from CLI/commands - Create and modify custom commands/mcp enable [server-name] - Enable an MCP server/mcp disable [server-name] - Disable an MCP serverShift+Enter - Add newlines for multi-line promptsCtrl+D - Exit CLI (requires double-press for safety)Ctrl+R - Review changes (press i for instructions, navigate with arrow keys)ArrowUp - Cycle through previous messagesRun the agent in a non-interactive mode, suitable for CI/CD pipelines:
agent -p 'Run tests and report coverage'
# or
agent --print 'Refactor this file to use async/await'
Output formats:
# Plain text (default)
agent -p 'Analyze code' --output-format text
# Structured JSON
agent -p 'Find bugs' --output-format json
# Real-time streaming JSON
agent -p 'Run tests' --output-format stream-json --stream-partial-output
Force mode (auto-apply changes without confirmation):
agent -p 'Fix all linting errors' --force
Media support:
agent -p 'Analyze this screenshot: screenshot.png'
CRITICAL: When running Cursor CLI from automated environments (AI agents, scripts, subprocess calls), the CLI requires a real TTY. Direct execution will hang indefinitely.
The Solution: Use tmux
# 1. Install tmux if not available
sudo apt install tmux # Ubuntu/Debian
brew install tmux # macOS
# 2. Create a tmux session
tmux kill-session -t cursor 2>/dev/null || true
tmux new-session -d -s cursor
# 3. Navigate to project
tmux send-keys -t cursor "cd /path/to/project" Enter
sleep 1
# 4. Run Cursor agent
tmux send-keys -t cursor "agent 'Your task here'" Enter
# 5. Handle workspace trust prompt (first run)
sleep 3
tmux send-keys -t cursor "a" # Trust workspace
# 6. Wait for completion
sleep 60 # Adjust based on task complexity
# 7. Capture output
tmux capture-pane -t cursor -p -S -100
# 8. Verify results
ls -la /path/to/project/
Why this works:
agent calls from subprocess/exec hang without TTYWhat does NOT work:
# ❌ These will hang indefinitely:
agent "task" # No TTY
agent -p "task" # No TTY
subprocess.run(["agent", ...]) # No TTY
script -c "agent ..." /dev/null # May crash Cursor
The agent automatically loads rules from:
.cursor/rulesAGENTS.mdCLAUDE.mdUse /rules command to create and edit rules directly from the CLI.
MCP servers are automatically loaded from mcp.json configuration.
Enable/disable servers on the fly:
/mcp enable server-name
/mcp disable server-name
Note: Server names with spaces are fully supported.
Perform a code review on the current changes or a specific branch:
agent -p 'Review the changes in the current branch against main. Focus on security and performance.'
Refactor code for better readability or performance:
agent -p 'Refactor src/utils.ts to reduce complexity and improve type safety.'
Analyze logs or error messages to find the root cause:
agent -p 'Analyze the following error log and suggest a fix: [paste log here]'
Automate git operations with context awareness:
agent -p 'Generate a commit message for the staged changes adhering to conventional commits.'
Run automated checks in CI pipelines:
# Set API key in CI environment
export CURSOR_API_KEY=$CURSOR_API_KEY
# Run security audit with JSON output
agent -p 'Audit this codebase for security vulnerabilities' --output-format json --force
# Generate test coverage report
agent -p 'Run tests and generate coverage report' --output-format text
Use context selection to analyze multiple files:
agent
# Then in interactive mode:
@src/api/
@src/models/
Review the API implementation for consistency with our data models