Skip to main content
Glama

validate_node

Read-onlyIdempotent

Validate n8n node configuration by checking required fields (minimal mode) or run comprehensive validation with errors, warnings, and suggestions (full mode).

Instructions

Validate n8n node configuration. Use mode='full' for comprehensive validation with errors/warnings/suggestions, mode='minimal' for quick required fields check. Example: nodeType="nodes-base.slack", config={resource:"channel",operation:"create"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoValidation mode. full=comprehensive validation with errors/warnings/suggestions, minimal=quick required fields check only. Default is "full"full
configYesConfiguration as object. For simple nodes use {}. For complex nodes include fields like {resource:"channel",operation:"create"}
profileNoProfile for mode=full: "minimal", "runtime", "ai-friendly", or "strict". Default is "ai-friendly"ai-friendly
nodeTypeYesNode type as string. Example: "nodes-base.slack"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
validYes
errorsNo
summaryNo
nodeTypeYes
warningsNo
displayNameYes
suggestionsNo
workflowNodeTypeNo
missingRequiredFieldsNoOnly present in mode=minimal
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, side-effect-free operation. The description adds behavioral context by explaining that 'full' mode returns errors/warnings/suggestions and 'minimal' does a quick required field check, going beyond the 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 concise with one informative sentence and an example. It is front-loaded with the purpose. Could be slightly more structured (e.g., bullet points for modes), but it is efficient and clear.

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

Completeness4/5

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

Given the tool has 4 parameters, enums, nested objects, and an output schema, the description covers the essential usage (modes, example) and the schema details each parameter. The output schema is not described but exists separately, so the description is sufficient for an AI to select and invoke the tool correctly.

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

Parameters4/5

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

Schema coverage is 100% with each parameter described. The description adds value by providing a concrete example (nodeType="nodes-base.slack", config={resource:"channel",operation:"create"}) that illustrates how parameters like nodeType and config interact, and explains mode values in context. This goes beyond the schema's individual descriptions.

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 'Validate n8n node configuration' with a specific verb and resource. It distinguishes from sibling tools like validate_workflow (for workflows) and get_node/search_nodes (for fetching/searching), making the tool's purpose unambiguous.

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

Usage Guidelines4/5

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

The description provides guidance on when to use 'full' vs 'minimal' modes and includes a concrete example. However, it does not explicitly compare to sibling tools like validate_workflow or search_templates for when not to use this tool, though the context implies the distinction.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mirza-javed/n8n-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server