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One command from a PDF to clean markdown and structured JSON: pulse extract invoice.pdf --schema invoice.json
The Pulse CLI brings the full extraction pipeline to your terminal. It talks to the same API as the platform and the MCP server, so your API key is the only credential, and anything you run is visible in your platform extraction library. 
uv tool install pulse-ai-cli
pulse login
pulse extract report.pdf

Command reference

Every command, flag, and workflow with examples.

Get an API key

Or skip it: pulse login fetches one through your browser.

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Install

uv tool install pulse-ai-cli
Installs the pulse command. Requires Python 3.11+.

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Log in

pulse login
Your browser opens the Pulse platform, you approve a short code (like ABCD-1234), and the CLI picks up your organization’s API key automatically. The key is validated and stored in your OS keychain. No browser handy? Use the key directly: 
pulse login --api-key sk_your_key_here
For CI and scripts, set PULSE_API_KEY in the environment instead; it takes precedence over the stored credential, and --api-key on any command beats both.

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Sixty-second tour

# Document in, markdown + JSON out (report.pulse.md / report.pulse.json)
pulse extract report.pdf

# Add a schema and get structured fields in the same run
pulse extract invoice.pdf --schema schemas/invoice.json

# No schema yet? Describe the fields and let Pulse draft one
pulse schema generate -p "vendor, line items, total due" -o schemas/invoice.json

# Whole folder, async; come back for results later
pulse extract ./contracts --no-wait
pulse jobs get <job_id> --watch

# Follow-ups reuse the extraction_id printed by extract
pulse tables <extraction_id>
pulse split <extraction_id> -t "financials:tables and figures"

# Check your plan and page usage
pulse usage
Every command takes --json for raw, pipe-safe output and -h for its full options. Running bare pulse starts an interactive shell with the same commands.

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Commands at a glance

CommandWhat it does
pulse extractDocuments (files, folders, URLs) to markdown and JSON; --schema adds structured output in one run.
pulse schema generateAI-draft or refine a JSON extraction schema from a prompt.
pulse schema applyRun a schema against a prior extraction or split.
pulse splitSplit a prior extraction into topic-based page ranges.
pulse tablesPull tables (HTML or JSON) out of a prior extraction.
pulse jobsWatch, resume, or cancel async jobs.
pulse usagePlan, pages used vs. allowance, and a breakdown by source.
pulse openOpen an extraction (or the dashboard) on the platform.
pulse whoami / login / logoutManage the stored credential.
See the command reference for full flags and examples.

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When to use the CLI

Use the CLI

You’re working hands-on in a terminal: one-off extractions, local files and folders, shell scripts, cron jobs, and CI steps where --json pipes straight into jq or the next tool.

Use the MCP server

You want an AI agent (Claude, Codex, VS Code) to read and structure documents on demand, deciding the steps itself.

Use the SDK / API

You’re building a production pipeline in your own application code with precise, repeatable control.

Use the Platform

You want a visual workspace to iterate on schemas, presets, and pipelines before automating them.

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Next steps

Command reference

Full flags, workflows, output conventions, and troubleshooting.

Structured output guidelines

Write schemas that extract reliably.