Borrowing it
Nothing to install: this file belongs to actions-marketplace-validations/AutomateLab-tech_n8n-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/actions-marketplace-validations/AutomateLab-tech_n8n-mcp/main/GEMINI.mdgit clone --depth 1 https://github.com/actions-marketplace-validations/AutomateLab-tech_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/instructions/actions-marketplace-validations/automatelab-tech_n8n-mcp/gemini-md)<a href="https://agentmods.dev/instructions/actions-marketplace-validations/automatelab-tech_n8n-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/actions-marketplace-validations/automatelab-tech_n8n-mcp/gemini-md/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/instructions/actions-marketplace-validations/automatelab-tech_n8n-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/actions-marketplace-validations/automatelab-tech_n8n-mcp/gemini-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00871 | $0.00871 |
| Opus 5 | $0.00436 | $0.00436 |
| Sonnet 5 | $0.00174 | $0.00174 |
| Haiku 4.5 | $0.00087 | $0.00087 |
Grade A, and why
AutomateLab-tech_n8n-mcp GEMINI.md 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 10d 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.
This is a copy
100% identical to n8n-mcp GEMINI.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
n8n-mcp
Use when the user wants to build, debug, or extend an n8n workflow - generating workflow JSON from a description, scaffolding a custom TypeScript node, building an AI agent (LangChain cluster), iterating over items, writing Code-node JS, linting an existing workflow, diagnosing a failed execution, or driving a live n8n instance via REST.
Pairs with the @automatelab/n8n-mcp server (loaded automatically by this extension). The server exposes 9 MCP tools; this context tells you when to use which.
Tool routing
Tool names use dot-notation: node.*, workflow.*, execution.* (renamed in v0.4.0 from n8n_*).
Stateless tools (work without any n8n instance):
workflow_generate- plain-English description -> workflow JSON. Detects AI-agent intent and emits a LangChain cluster.node_scaffold- description -> singleINodeTypeTypeScript file for a custom n8n package.workflow_lint- workflow JSON -> list of issues (deprecated types, missingtypeVersion, broken connections, AI Agent withoutai_languageModel, IF v1 schema, etc.).execution_explain- failed/surprising execution JSON -> diagnosis. Catches the #1 n8n pain point: items "silently disappearing" between nodes. Also flags unresolved={{ ... }}expressions and surfaces LLM token usage.
Live-instance tools (require N8N_API_URL + N8N_API_KEY env vars):
workflow_list- paginate workflows; filter by active/tags/name.workflow_get- fetch a workflow by id. Pair withworkflow_lintto audit deployed workflows.workflow_create- POST a generated workflow. Strips read-only fields. Workflow is created inactive.workflow_activate- flip active on/off.execution_list- browse executions; passincludeData: truefor the full body. Pair withexecution_explain.
Default chains:
- Generate, then ship:
workflow_generate->workflow_lint-> (if env configured)workflow_create->workflow_activate. - Audit a deployed workflow:
workflow_list->workflow_get->workflow_lint. - Diagnose a failure:
execution_list {status: "error"}-> pick one ->execution_list {includeData: true, ...}->execution_explain.
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.
- 10d ago First seen · 56 lines · 871 tokens per session scan A 5511954e7956
AutomateLab-tech_n8n-mcp GEMINI.md is an instructions file published in the GitHub repository actions-marketplace-validations/AutomateLab-tech_n8n-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 871 tokens to every session, about $0.0044 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to n8n-mcp GEMINI.md, differing in 0 lines, and is treated as a copy.
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