How do I monitor xAI Grok CLI sessions?

Install ClawMetry (pip install clawmetry). The daemon auto-detects Grok and renders every session, tool call, model, and token in one dashboard at http://localhost:8900.

Can I see what Grok actually uploaded to xAI?

Yes. Grok stages outbound repo payloads before uploading them. ClawMetry surfaces what is staged so you can audit what left your machine (files, sizes, timestamps) and flag any surprisingly large payloads before the session repeats.

Does ClawMetry track Grok cost per model?

Yes. Grok routes between Grok Fast, Grok Beta, and Grok Code models; every turn is labelled with the model id and per-model spend rolls up on the Cost tab.

Is ClawMetry safe to point at a running Grok install?

Yes. ClawMetry only observes. It never writes to Grok, and it stays fast even on a long session history.

How much does ClawMetry cost for Grok?

Free forever on your own machine. Cloud starts at $9/node/mo (Starter) or $19/node/mo (Pro).

Grok × ClawMetry

Observability and cost tracking for xAI Grok

See every Grok CLI session, tool call, and token as it happens. ClawMetry detects Grok automatically and renders sessions, tokens, cost, and outbound repo payloads (so you see what left your machine) in one dashboard.

Supported runtime Zero config, auto-detected Read-only Free trial Official Grok site ↗

📦 631k+ installs 🌍 128+ countries ⭐ 392 on GitHub 🏆 #5 Product Hunt

What ClawMetry sees on Grok

Once ClawMetry is running, your Grok activity shows up as:

Sessions: started at, last activity, model, message count, per-session token totals.
Live activity: every tool call as it lands, with args and result. Turn-level tokens split.
Per-turn tokens: Per-turn tokens written by Grok (input, output, plus cached tokens on cache-supported Grok models).
Cost per session, per model, per hour: cache-aware where the model supports caching.
Outbound repo-payload attribution (see what actually left your machine): the Grok-specific signal ClawMetry surfaces that generic dashboards do not.
Approval and kill switch: watch for token-maxing signals (message repeat, no-progress heuristic, cost-per-hour threshold), pause or kill before the next call.

Enable it in about two minutes

1. Install ClawMetry

Pick the line that matches your OS. Windows users: paste the install.cmd line, not the shell one.

# macOS or Linux
curl -fsSL https://clawmetry.com/install.sh | bash

# Windows (cmd.exe or PowerShell)
curl -fsSL https://clawmetry.com/install.cmd -o install.cmd && install.cmd

Already have Python? pip works too; onboard is the interactive first-run wizard.

# Any OS with Python 3.9+
pip install clawmetry && clawmetry onboard

Or skip the terminal entirely and grab the desktop app: macOS (.dmg) · Windows (.exe) · Linux (.AppImage). It installs and updates ClawMetry for you.

2. Run the daemon

clawmetry

The daemon auto-detects Grok and starts reading immediately. No env var, no config, no runtime restart.

3. Open the dashboard

Open http://localhost:8900. Switch the runtime chip to Grok.

Start the free trial →

The one thing this catches that Grok alone does not

Left alone, Grok's failure mode is a session that stages an unexpectedly large repo payload for upload and you never notice. ClawMetry watches for it: cost per hour on the Grok runtime, message-repeat detection, and per-session token-growth curves. Set a threshold, and the approval queue pauses before the next call. Kill switch (Pro) stops it.