Screenpipe Cli
Manage Screenpipe AI automation pipes and service connections via CLI
What You Can Do
You can create, list, enable, disable, and run markdown-based AI automation pipes that execute on schedules ranging from every 30 minutes to custom cron expressions. Manage service connections to Telegram, Slack, Discord, and other platforms directly from the CLI, and troubleshoot pipe execution with built-in logging and debugging commands.
Features
view enabled/disabled status in a compact table format
toggle automation on or off without deletion
test pipes before scheduling without waiting
troubleshoot failures with detailed pipe logs
quickly deploy community pipes or custom automations
use human-readable schedules (every 30m, every monday at 9am) or cron expressions
list available models for your pipe automations
remove automations and their configurations cleanly
Example Output
Example 1: List all pipes
bun x screenpipe@latest pipe list
Outputs:
| Name | Enabled | Schedule | Last Run |
|---|---|---|---|
| daily-summary | ✓ | every day at 9am | 2h ago |
| slack-alerts | ✓ | every 30m | 5m ago |
| archive-emails | ✗ | every friday at 5pm | Never |
Example 2: Run a pipe immediately for testing
bun x screenpipe@latest pipe run daily-summary
Executes the daily-summary pipe instantly and returns the output.
Example 3: View logs for debugging
bun x screenpipe@latest pipe logs slack-alerts
Displays timestamped execution logs, errors, and output from the last 10 runs.
What's Included
- screenpipe-cli SKILL.md: Complete command reference and pipe structure documentation
- Pipe template: Ready-to-use markdown template with YAML frontmatter and schedule syntax examples
- Service connection guide: Configuration instructions for Telegram, Slack, Discord integrations
- Schedule syntax cheatsheet: Human-readable and cron expression examples for all frequency patterns
- Debugging checklist: Common issues and troubleshooting steps for pipe failures
Who It's For
- DevOps engineers — automate monitoring, alerting, and log processing workflows
- Software developers — schedule AI-powered code analysis and documentation tasks
- System administrators — manage scheduled automation pipelines with service integrations
- AI automation builders — create and deploy custom AI agent workflows without backend infrastructure
- Data engineers — build scheduled data processing and notification pipelines
Best For
- Creating scheduled AI automations that run on fixed intervals or cron schedules
- Integrating AI agents with chat platforms (Slack, Discord, Telegram) for notifications
- Testing and debugging pipe automations before production deployment
- Managing multiple automation pipelines from a single CLI interface
- Deploying community-built pipes or forking existing automations from GitHub
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