n8n-mcp

Server Quality Checklist

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Latest release: v2.63.0
Disambiguation5/5
Each tool has a clearly distinct purpose: get_node and get_template fetch details, search_nodes and search_templates search, tools_documentation provides MCP documentation, validate_node and validate_workflow perform validation. No overlap.
Naming Consistency4/5
Most tools follow verb_noun snake_case pattern (get_node, search_nodes, etc.). tools_documentation is a slight deviation (noun_noun), but still readable and not confusing.
Tool Count5/5
7 tools is well-scoped for a server focused on node/workflow exploration and validation. Each tool earns its place without redundancy.
Completeness4/5
The tool set covers retrieval, search, validation, and documentation for nodes and templates. Missing a 'list all' function and mutation operations, but this appears intentional for a read/validate server.
Average 4.3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 69 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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}
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds that it returns documentation but no additional behavioral traits beyond the implied read-only nature from annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, and each sentence adds distinct value. No redundant or unnecessary words.
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?
For a simple tool with two optional parameters and no output schema, the description covers the main use cases. It could mention that the output is documentation text, but the purpose is clear. The annotations provide additional safety context.
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 description coverage is 100%, so the schema already documents the parameters. The description adds usage context (e.g., 'use topic parameter to get documentation for specific tools') but does not add meaning beyond what the schema provides. Baseline 3 is appropriate.
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 the tool's purpose: 'Get documentation for n8n MCP tools.' It distinguishes from siblings by specifying it covers tool documentation, not node or template details. The two usage modes (quick start vs. specific/comprehensive) are immediately clear.
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 explicit guidance on when to use each parameter: call without parameters for a quick start guide, use topic for specific tools, and depth='full' for comprehensive docs. It does not explicitly mention when not to use the tool, but the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint, indicating safe read-only operation. The description adds behavioral context by explaining how the mode parameter controls response size (nodes_only, structure, full), which is useful 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no wasted words. It front-loads the purpose and then explains the mode parameter, making it easy to scan.
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?
For a simple read tool with two parameters and no output schema, the description covers the essential behavior. It lacks explicit mention of return format (e.g., template object), but the mode descriptions imply it returns workflow data. Minor gap, but overall adequate.
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%, and both parameters are fully described. The description adds a concise summary of the mode options but no new semantic information beyond what the schema provides. Baseline 3 is appropriate.
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 'Get template by ID' with a specific verb and resource. It distinguishes from sibling tools like search_templates (search vs get by ID) and get_node (different resource). The mode parameter further clarifies the response granularity.
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 implies usage when you have a specific template ID. It does not explicitly exclude other scenarios or compare to search_templates, but the purpose is clear enough. A brief note on when not to use it (e.g., searching) would improve it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses return limit (max 20 results) and the effect of includeExamples (top 2 template configs). The annotations already declare readOnlyHint and idempotentHint, so the tool is safe. The description adds useful behavioral details beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4 sentences) and front-loaded with the main action. Every sentence adds value: search purpose, parameter usage, limit, and examples option. No superfluous text.
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 6 parameters and no output schema, the description covers input usage well but lacks details on return format, sorting, or pagination beyond the limit. It is mostly complete for a search tool, but could mention whether results are sorted by relevance.
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% with descriptions for all parameters, so baseline is 3. The description provides a usage example for 'query' and paraphrases the intent of includeExamples, but adds minimal new semantic value beyond what the schema already offers.
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 it searches n8n nodes by keyword with optional examples. It distinguishes from sibling tools like 'get_node' (which retrieves a specific node) and 'search_templates' (which searches templates) by specifying that it searches nodes and can optionally include template configurations.
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 explicit usage instructions (e.g., 'Pass query as string. Example: query="webhook" or query="database".') and explains when to use optional parameters. However, it does not explicitly state when not to use this tool or list alternatives, but given the sibling context, the guidance is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations readOnlyHint=true and idempotentHint=true already indicate safety. Description adds behavioral clarity about mode behavior, but doesn't mention pagination or rate limits. No contradiction 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 long sentence that front-loads the core purpose. It could be more structured (e.g., bullet points) but remains concise given the complexity. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While schema covers parameters, the description does not describe the response format or pagination behavior. With no output schema, the description should hint at what the response contains. This is a gap, but the tool is read-only and search-oriented, so moderate completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description enhances understanding by linking parameters to specific search modes (e.g., 'For searchMode=by_nodes: array of node types'). This adds value beyond schema.
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 the tool searches templates and lists five distinct search modes. It distinguishes from sibling tools like search_nodes and get_template by focusing on templates and detailing mode-specific purposes.
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 explicitly tells when to use each search mode (e.g., 'Use searchMode='keyword' for text search'). It implicitly differentiates from siblings by focusing on templates. Missing explicit 'when not to use' but sufficient for typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds significant value by disclosing token estimates for each detail level (e.g., ~200 tokens for minimal, ~1-2K for standard), output types per mode (e.g., markdown for docs), and combining parameters. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose. Each sentence adds unique information: overview, detail/mode explanations, and usage tips. No redundant or vague statements.
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?
The description covers modes, detail levels, token costs, and parameter combinations well, but it doesn't explicitly describe the overall output format (e.g., JSON structure for standard info mode). Given no output schema, a brief mention of return shape would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds meaningful context beyond parameter descriptions, such as token size expectations for detail, usage examples (e.g., 'Use format='docs'), and combining mode with propertyQuery. This helps the agent make informed parameter choices.
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 'Get node info' with specific verb and resource. It details progressive detail levels and multiple modes (info, docs, search_properties, versions, etc.), which distinguishes this tool from siblings like get_template or search_nodes. The purpose is unambiguous and well-defined.
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 provides internal usage guidance (e.g., 'Use format='docs' for readable documentation, mode='search_properties' with propertyQuery for finding specific fields') but does not explicitly address when to use this tool versus sibling tools like search_nodes or get_template. Missing cross-tool alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnly and idempotent; description adds behavioral detail like returning errors/warnings/fixes and being essential before deployment. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first defines tool, second gives purpose (before deploy). Front-loaded with key information; no fluff.
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?
With output schema present, description appropriately covers validation scope and use case. Adds detail about AI tools validation not in schema.
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%, so baseline 3. Description does not add parameter-level detail beyond what schema already provides.
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?
Description clearly states 'Full workflow validation' and lists specific aspects: structure, connections, expressions, AI tools. Distinguishes from sibling 'validate_node' by scope.
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?
Explicitly says 'Essential before deploy', providing usage context. Lists validation categories, but lacks explicit when-not-to-use or mention of alternatives.
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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