io.github.ratamaha-git/n8n-mcp

MCPcommunity
v0.3.0io.github.ratamaha-gitUnknownUpdated 3mo 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 →
3mo agoLast update
Package
Authorio.github.ratamaha-git
LicenseUnknown
Version0.3.0
Sourcemcp-registry
Trust Status
B
60/100Good
Listed in Forge index+10/10
Publisher identity verified+0/20
Publisher: run `forge publish` from the package repo to claim ownership
Ed25519 publish signature+0/5
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>" }
npm Trusted Publishing (Sigstore)+0/5
Publish from GitHub Actions with --provenance so the attestation binds this package to this repo
npm maintainer match+0/5
Earned once your identity is verified above and that login is an npm maintainer of this package
CVE scan · clean+30/30
Static analysis · clean+20/20
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 · 2mo ago
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