io.github.ratamaha-git/n8n-mcp

MCPcommunity
v0.3.0io.github.ratamaha-gitUnknownUpdated 1mo agonpmGitHub

MCP server for n8n: generate, lint, explain failed executions, drive live n8n via REST.

An MCP server for n8n that gives Claude, Cursor, and other AI agents tools for generating workflows, linting, diagnosing failed executions, and driving live n8n instances. We use n8n daily inside AutomateLab and kept hitting the same LLM failures: workflow JSON that imports but fails at runtime, AI Agent clusters wired with the wrong connection types, executions that silently drop items with no…

Automatically indexed from public sources. Not yet verified by the developer on Forge.Claim this listing →
1mo agoLast update
Package
Authorio.github.ratamaha-git
LicenseUnknown
Version0.3.0
Sourcemcp-registry
npm@automatelab/n8n-mcp
GitHubratamaha-git/n8n-mcp
Trust Status
B
60/100Good
✓Listed in Forge index+10/10
—Publisher identity verified+0/25
→ Publisher: run `forge publish` from the package repo to claim ownership
—Ed25519 publish signature+0/10
→ Included automatically when the publisher runs `forge publish`
—Domain verification+0/5
→ Publisher: host /.well-known/forge.json on the package homepage with { "publisher": "<github-login>" }
✓CVE scan · clean+30/30
✓Static analysis · clean+20/20
—npm provenance (Sigstore)+0/5
→ Publish from GitHub Actions with the --provenance flag
Paste into Claude Code, Cursor, or any AI assistant to fix all gaps
StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain—
Provenance—
Dependencies60 resolved · 1 with advisories
Tool surface—
Security scan✓ Cleanv1.1.0 · 20d ago
DEPundici@5.29.0GHSA-2mjp-6q6p-2qxm, GHSA-4992-7rv2-5pvq, GHSA-g9mf-h72j-4rw9 (transitive)
EvalsNone
IndexedJun 13, 2026

Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts — it cannot prove the absence of malicious code.

About

An MCP server for n8n that gives Claude, Cursor, and other AI agents tools for generating workflows, linting, diagnosing failed executions, and driving live n8n instances. We use n8n daily inside AutomateLab and kept hitting the same LLM failures: workflow JSON that imports but fails at runtime, AI Agent clusters wired with the wrong connection types, executions that silently drop items with no clue where to look. Dumping the whole n8n catalog into context doesn't fix it - the failure modes are…

Keywords
mcp