AutomateLab n8n MCP

Lint an n8n workflow JSON

workflow_lint

Read-onlyIdempotent

Lint an n8n workflow JSON. Returns concrete errors and warnings: missing credentials, deprecated node types (Function -> Code, spreadsheetFile -> convertToFile/extractFromFile), broken connections, missing or non-numeric typeVersion, duplicate node names or IDs, AI Agent missing ai_languageModel sub-node, Webhook missing webhookId, IF node still on v1 condition schema, rate-sensitive nodes without retries, Code-node sandbox violations, expression staleness ($('NodeName') referencing missing nodes), manualTrigger in active workflows, disabled-but-wired nodes, empty Set nodes, HTTP method/body mismatches, Schedule trigger DST risk, credential drift, webhook test paths in active workflows. Deterministic, rule-based.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`workflow`	Yes	n8n workflow as either a parsed object or a JSON string (will be parsed).

Output Schema

TableJSON Schema

Name	Required	Description
`issues`	Yes	All lint findings, ordered by node.
`error_count`	Yes	Number of error-severity issues.
`warning_count`	Yes	Number of warning-severity issues.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only and idempotent behavior. The description adds value by listing the specific rules and checks performed, and states 'Deterministic, rule-based,' which aligns with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that front-loads the main purpose and then lists checks. It is informative but could be more structured (e.g., bullet points) for easier scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all necessary aspects: input, examples of checks, deterministic nature. Given that an output schema likely describes return values, no further details are needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single parameter 'workflow'. The description adds minimal extra meaning beyond the schema's description, essentially restating it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Lint an n8n workflow JSON' and enumerates specific checks, distinguishing it from sibling tools focused on execution, activation, or creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool over alternatives. While the context of linting is implied, there is no direct guidance on prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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