Woow n8n MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: node info vs node search, node validation vs workflow validation, template retrieval vs template search, and meta documentation. No two tools overlap in function.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (get_node, search_nodes, validate_node, etc.), but 'tools_documentation' deviates as a noun pair. The inconsistency is minor and does not significantly impact readability.
Tool Count5/5
With 7 tools, the server is well-scoped for its n8n-focused purpose. Each tool serves a necessary function, covering node exploration, validation, and template access without bloat.
Completeness4/5
The tool set covers the core lifecycle of node discovery, detailed info, validation, and template search/retrieval. Minor gaps exist, such as no tool for listing or creating workflows, but for an assistant-style server, the coverage is strong.
Average 4.2/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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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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 declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds parameter-dependent behavior contexts (quick start vs specific tool docs vs comprehensive docs), which is useful. However, it does not disclose additional behavioral details like output format, pagination, or error handling, but for a documentation tool these are less critical. The description does not contradict annotations, and the added context is modest.
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, with the purpose stated in the first sentence and usage instructions in the next two. Every sentence provides essential information, with no waste or redundancy. It is appropriately front-loaded and efficiently communicates the core functionality and options.
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's simplicity (no required params, no output schema), the description is nearly complete. It covers all usage modes (no params, topic, depth) and mentions the quick start guide. The only minor gap is not describing the output format (e.g., markdown vs plain text), but for a documentation tool this is not a significant omission. Overall it is sufficiently complete for an agent to select and invoke correctly.
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%, with both depth and topic already described in detail (e.g., depth enum values and topic examples). The description repeats similar guidance ('Use depth="full" for comprehensive documentation' mirrors the schema's 'full' meaning). It adds minimal extra meaning beyond the schema, so the baseline of 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 function: 'Get documentation for n8n MCP tools.' This specifies the verb (Get) and resource (documentation for MCP tools), and distinguishes from siblings like get_node or search_nodes which operate on actual data, not documentation. The mention of a quick start guide and depth levels further clarifies 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?
The description gives explicit usage scenarios: 'Call without parameters for quick start guide', 'Use topic parameter to get documentation for specific tools', and 'Use depth="full" for comprehensive documentation.' This provides clear context for when to use different parameter combinations. It doesn't explicitly state exclusions or alternatives, but the guidance is strong enough to make the tool's usage obvious.
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 and idempotentHint, so the description doesn't need to state safety. It adds useful behavioral context about the mode affecting response size, which goes beyond the schema by framing it as size control. No contradictions 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every sentence adds value. No fluff or repetition of the schema.
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's simplicity, a 100% schema coverage, and read-only annotations, the description is adequately complete. It explains the core purpose and the mode parameter's effect. No output schema exists, but the description's reference to 'complete workflow' provides a minimal sense of return content.
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 both parameters fully described in the schema. The description only restates the mode options ('minimal', 'nodes+connections', 'complete workflow') without adding new semantics beyond what the schema already provides. Therefore, 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 states a specific verb+resource: 'Get template by ID', clearly distinguishing it from sibling tools like get_node and search_templates. It also mentions the mode parameter that affects response detail, making the tool's scope even clearer.
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 clearly implies when to use this tool (when you have a template ID) and explains how mode controls response size. It doesn't explicitly list exclusions or alternatives, but the context is clear enough for an agent to differentiate it from search tools.
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, so the safety profile is covered. The description adds valuable behavior details: max 20 results, includeExamples behavior, and the token trade-off for includeOperations (saves a get_node round-trip). This goes beyond what annotations provide.
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 compact at three sentences, front-loaded with the main purpose, and every sentence adds value. It includes an example and key behavioral constraints without fluff.
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's complexity (6 params, no output schema), the description covers the essential behaviors: search scope, max results, and optional enrichments. It does not describe the result structure, but for a search tool with schema-documented params, this is sufficient. Sibling context further fills gaps.
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 all six parameters adequately. The description adds a concrete example and clarifies includeExamples, but this is marginal value 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 searches n8n nodes by keyword, with an explicit verb and resource. It distinguishes itself from siblings like get_node (fetch specific node details) and search_templates (search templates) by focusing on node discovery.
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 clear usage context with examples ('Pass query as string. Example: query="webhook"') and explains when to use optional flags like includeExamples and includeOperations. However, it does not explicitly state when to prefer this over get_node or search_templates, though the sibling names imply the distinction.
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 provide readOnlyHint and idempotentHint, and the description aligns with them. The description adds context about the patterns mode ('lightweight workflow pattern summaries mined from 2700+ templates') and the multi-mode behavior, going beyond the structured 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 only two sentences, front-loaded with the verb and resource. The second sentence efficiently lists all five modes with their use cases, with no wasted 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?
The tool is complex (13 params, 5 modes, no output schema), but the schema covers parameter details. The description gives enough context to choose a mode and understand the tool's scope, though it could explicitly mention mode-specific parameter requirements or response format.
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 baseline is 3. The description mirrors the searchMode enum descriptions from the schema and adds only the '2700+ templates' detail. It does not provide additional meaning for other parameters like query, nodeTypes, or limit beyond what the schema already has.
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: 'Search templates with multiple modes.' It distinguishes itself from siblings like get_template (retrieval) and search_nodes (node search) by explicitly targeting templates and enumerating all five search modes.
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?
It provides explicit mode-specific usage guidance (keyword for text search, by_nodes for specific nodes, etc.), which helps the agent select the right mode. However, it does not mention when to prefer alternative tools like get_template for direct retrieval.
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 and idempotentHint, covering safety. The description adds meaningful context by explaining that full mode returns errors/warnings/suggestions and minimal mode performs a quick required-fields check, disclosing the validation behavior and output type beyond 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 concise: two sentences plus an example. It front-loads the primary purpose and then provides mode selection guidance and a practical example. Every element contributes useful information without redundancy.
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 an output schema present, return values are already defined. The description covers the tool's purpose, mode selection, and an example, while the schema fully documents all parameters. Annotations cover safety. Together, this provides complete context for an agent 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?
The schema already provides descriptions for all 4 parameters (100% coverage), so the description need not repeat them. It adds value with a concrete example (nodeType="nodes-base.slack", config={resource:"channel",operation:"create"}) that illustrates the expected format, going beyond the schema's basic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates n8n node configuration with a specific verb and resource. The example with nodeType and config clarifies its purpose. However, it does not explicitly distinguish from sibling tools like validate_workflow or get_node, so it falls short of a 5.
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 clear guidance on when to use 'full' versus 'minimal' mode, which helps the agent choose appropriate parameters. It does not mention when to use this tool over alternatives (e.g., validate_workflow), so it lacks explicit exclusion or alternative tool guidance.
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 and idempotentHint, lowering the bar. The description adds behavioral context by stating it returns 'errors/warnings/fixes', which informs the agent about the output nature. No contradictions with annotations. It could mention lack of side effects or performance implications, but the annotations cover safety.
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 two sentences, extremely concise and front-loaded with the primary purpose. Each word adds value: scope, aspects, expected return, and timing. No filler or redundant information.
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?
With a full schema (including output schema) and rich annotations, the description is largely sufficient. It covers what is validated, what is returned, and when to use. It does not mention the options parameter, but the schema fully documents that. A tiny gap is the lack of mention of profile choices, but this is a minor omission given schema completeness.
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 baseline 3 applies. The description's mention of 'connections, expressions' loosely aligns with the validateConnections and validateExpressions options, but it does not add meaning beyond what the schema already provides for the workflow parameter or options parameter. Schema does the heavy lifting.
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 specifies the tool's function as 'Full workflow validation', enumerating the validated aspects (structure, connections, expressions, AI tools). This specific scope distinguishes it from the sibling 'validate_node' tool, which validates individual nodes. The verb+resource+scope is precise and 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 states 'Essential before deploy', providing a clear contextual trigger for when to use the tool. It does not explicitly name alternatives or exclusions, but the 'full workflow' framing implies a complementary role to node-level validation tools. The deployment context is strong enough to guide the agent.
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 read-only and idempotent behavior, so the safety profile is covered. The description adds valuable behavioral context by disclosing token ranges for each detail level, indicating response size, and clarifying that modes return different formats (e.g., markdown docs). This goes 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 compact (three sentences) and front-loads the core purpose, then efficiently describes details and usage tips. Every sentence is informative, with no filler.
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?
With no output schema, the description partially explains return characteristics via token estimates and mode outputs, but it does not fully detail the response structure for each mode. The description covers most relevant dimensions (modes, detail, parameters) but could be more explicit about the differences between version-related modes.
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?
Despite 100% schema coverage, the description adds meaningful parameter relationships, such as connecting mode='search_properties' with propertyQuery and providing token estimates for detail levels. However, it incorrectly uses 'format' instead of 'mode' in one tip, which could cause minor confusion.
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 function with a specific verb ('Get') and resource ('node info'), and enumerates distinct modes (info, docs, search_properties, versions) that differentiate it from search/validation tools. The phrase 'progressive detail levels' further clarifies the 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?
The description provides clear guidance on when to use specific modes ('Use format='docs' for readable documentation, mode='search_properties' with propertyQuery') but does not explicitly compare this tool to siblings like search_nodes or validate_node. The context implies that get_node is for retrieving details of a known node type, not for discovering nodes.
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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