n8n-MCP is a Model Context Protocol server that gives AI assistants structured knowledge of n8n's workflow-automation nodes, including their properties, operations, documentation, and examples. It helps developers use AI assistants to create and work with n8n workflows. The catalogue contains skills, agents, and instructions for using it.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add czlonkowski/n8n-mcp --skill n8n-error-handlinggit clone --depth 1 https://github.com/czlonkowski/n8n-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/czlonkowski/n8n-mcp/n8n-error-handling)<a href="https://agentmods.dev/skills/czlonkowski/n8n-mcp/n8n-error-handling"><img src="https://agentmods.dev/badge/skills/czlonkowski/n8n-mcp/n8n-error-handling/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/czlonkowski/n8n-mcp/n8n-error-handling"><img src="https://agentmods.dev/badge/skills/czlonkowski/n8n-mcp/n8n-error-handling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00128 | $0.04649 |
| Opus 5 | $0.00064 | $0.02325 |
| Sonnet 5 | $0.00026 | $0.00930 |
| Haiku 4.5 | $0.00013 | $0.00465 |
Grade A, and why
n8n-error-handling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- n8n-error-handling — 100% identical, 0 lines differ
- n8n-error-handling — 100% identical, 0 lines differ
- n8n-error-handling — 100% identical, 0 lines differ
- n8n-error-handling — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
n8n Error Handling
By default, when an n8n node throws, the whole workflow halts. For an interactive run you're watching, that's fine — you see the red node and fix it. For anything unattended (a webhook API, a cron job, a queue worker, an agent tool), it's the wrong default: the caller gets a timeout or an empty 500, the operator gets no alert, and the symptom is "the integration just stopped working" with no log and no clue.
This skill is about making failures loud, structured, and recoverable — and, best case, self-healing so transient blips never reach a human at all.
The two ideas that prevent most silent failures:
- Per-node error outputs — a node's failure routes down a second output you control, instead of killing the run.
- A workflow-level error workflow — a catch-all that fires for anything that escapes per-node handling (timeouts, crashes between nodes, unwired failures).
When you actually need this
| Workflow shape | Error handling posture |
|---|---|
Webhook / API (anything with Respond to Webhook) |
Required. Every fallible node's error output wired; status code matches cause. |
| Scheduled / cron / queue worker / agent tool (unattended) | Required. A workflow-level error workflow, plus retryOnFail on network nodes. |
| Internal one-off you run and watch yourself | Optional. Default onError: "stopWorkflow" is fine — you'll see the red node and re-run. |
The dividing line: if anyone other than you sees the output — a downstream system, an end user, an on-call engineer — the failure has to be handled, not swallowed. If you're the only watcher and the cost of failure is "I notice and re-run", looser is fine.
The #1 silent trap: per-node error output is a TWO-step setup
This is the single most common way an n8n workflow "handles" errors while actually swallowing them. Routing a node's failure to a handler takes two changes, and doing only one looks complete but misbehaves:
- Set
onError: "continueErrorOutput"on the node. This is what creates the second output. Without it,main[1]doesn't exist no matter what you wire. - Wire that error output (
connections.<node>.main[1], i.e.sourceIndex: 1) to a real handler. Without a target, the error data is emitted into the void.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 270 lines · 128 tokens per session scan A 0a2a0e4574e7
n8n-error-handling is a skill published in the GitHub repository czlonkowski/n8n-mcp (22,861 stars, last pushed yesterday), licensed MIT. It adds 128 tokens to every session and 4,649 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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