How do I monitor n8n AI workflows?

Install ClawMetry (pip install clawmetry). The daemon auto-detects n8n and renders every workflow execution, AI node call, and per-node token spend in one dashboard at http://localhost:8900.

Does ClawMetry work with n8n's LangChain nodes and OpenAI nodes?

Yes. Both carry usage metadata on their execution output; ClawMetry normalises both so per-node cost is directly comparable.

Can I see cost per n8n workflow, per hour?

Yes. The Cost tab groups by workflow id and shows per-workflow, per-hour token spend. Set an alert on a per-workflow budget and the approval queue pauses subsequent executions.

Does ClawMetry catch a scheduled n8n workflow that loops overnight?

Yes. n8n's cron trigger fires executions on schedule; ClawMetry watches execution frequency and per-execution token growth. A workflow whose token spend accelerates hour-over-hour is flagged, and the kill switch (Pro) can pause future scheduled executions.

How much does ClawMetry cost for n8n?

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

n8n × ClawMetry

Observability and cost tracking for n8n AI workflows

See every n8n AI workflow execution, node call, and token as it happens. ClawMetry detects n8n automatically and renders workflow runs, per-node cost, and per-provider token spend in one dashboard.

Supported runtime Zero config, auto-detected Read-only Free trial Official n8n site ↗

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

What ClawMetry sees on n8n

Once ClawMetry is running, your n8n 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-node usage extracted from n8n's AI node executions (LangChain nodes carry the LangChain usage shape; OpenAI Chat nodes carry the OpenAI shape).
Cost per session, per model, per hour: cache-aware where the model supports caching.
Per-workflow-node cost attribution (which AI node in which workflow spent how many tokens): the n8n-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 n8n 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 n8n.

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The one thing this catches that n8n alone does not

Left alone, n8n's failure mode is a scheduled n8n workflow that quietly runs an OpenAI node in a loop through the weekend. ClawMetry watches for it: cost per hour on the n8n 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.