Noun MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. For example, 'get_icon' retrieves metadata for a specific icon, while 'download_icon' handles downloading it, and 'search_icons' searches across icons. The descriptions clearly differentiate between operations on icons versus collections, and between retrieval, search, and utility functions.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern using snake_case, such as 'check_usage', 'download_icon', and 'search_collections'. The naming is predictable and readable throughout, with no deviations in style or convention, making it easy for agents to understand and use the tools.
Tool Count5/5With 7 tools, the count is well-scoped for a Noun Project API server. Each tool earns its place by covering distinct aspects like usage checking, icon retrieval, downloading, searching, and collection management. This is neither too sparse nor bloated, fitting typical MCP server ranges for focused domains.
Completeness4/5The tool surface is nearly complete for the Noun Project domain, covering key operations like searching, retrieving, and downloading icons, as well as managing collections. A minor gap exists in update or delete operations (e.g., no tools for modifying collections or icons), but agents can work around this as the core workflows are well-supported.
Average 3.1/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions retrieving 'details and icons' but lacks critical information such as whether this is a read-only operation, potential rate limits, authentication requirements, or how pagination works with 'next_page' and 'prev_page' parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for the complexity, with every part contributing to clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return format, pagination behavior, or error handling, leaving significant gaps in understanding how to effectively use the tool beyond basic parameter input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond implying retrieval of 'details and icons', which loosely relates to parameters like 'thumbnail_size' and 'include_svg', but doesn't enhance understanding of their semantics beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'details and icons of a specific collection', making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_collections' or 'get_icon', which might retrieve similar data but with different scopes or filters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare to siblings like 'search_collections' for broader queries or 'get_icon' for individual icons, leaving usage context ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on traits like rate limits, authentication needs, response format, or error handling. For a tool with zero annotation coverage, this is a significant gap, as the agent has no insight into operational constraints or expected behavior beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get autocomplete suggestions') without any wasted words. It's appropriately sized for a simple tool, making it easy for an agent to parse quickly. Every part of the sentence contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for effective tool use. It covers the basic purpose but omits critical context like response format, error cases, or performance hints. For a tool with 2 parameters and no structured behavioral data, the description should provide more guidance to compensate, but it falls short.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for both parameters ('query' and 'limit'), so the schema does the heavy lifting. The description adds no additional meaning beyond implying a search context, which is already covered by the schema. This meets the baseline score of 3 for high schema coverage without extra param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('autocomplete suggestions for icon search'), making it immediately understandable. It distinguishes from siblings like 'search_icons' by focusing on autocomplete suggestions rather than full search results. However, it doesn't explicitly contrast with 'search_collections' or other siblings, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'search_icons' or 'get_icon'. It mentions 'autocomplete suggestions' but doesn't specify use cases (e.g., for real-time search assistance) or exclusions. Without any contextual cues, the agent must infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool's purpose but doesn't describe key behaviors like pagination (implied by 'next_page' and 'prev_page' parameters but not explained), rate limits, authentication needs, or what the search returns (e.g., list of collections with metadata). This is inadequate for a search tool with multiple parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search tool with pagination parameters and no output schema, the description is insufficient. It doesn't explain the return format (e.g., what data fields are included), how results are ordered, or error handling. With no annotations and missing output details, it leaves significant gaps for the agent to infer behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 parameters ('query', 'limit', 'next_page', 'prev_page') with descriptions. The description adds no additional meaning beyond what's in the schema, such as explaining how pagination tokens work or default limits. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search for collections') and the target resource ('collections on The Noun Project'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search_icons' or 'get_collection', which would require mentioning what makes this tool distinct (e.g., searching vs. retrieving a specific collection).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'search_collections' over 'get_collection' (for specific collections) or 'search_icons' (for icons), nor does it specify prerequisites or exclusions. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions filtering options but doesn't describe critical behaviors like pagination (implied by 'next_page'/'prev_page' parameters), rate limits, authentication needs, or what the response format looks like. This is inadequate for a search tool with 9 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and briefly mentions key capabilities. Every word earns its place with zero redundancy or wasted space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the search results format, pagination behavior, error conditions, or usage constraints. For a search tool with rich filtering options, this leaves significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 parameters thoroughly. The description adds marginal value by listing some filterable attributes ('style, line weight, public domain, and more') but doesn't provide additional semantics beyond what's in the schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search for icons on The Noun Project.' It specifies the verb ('search') and resource ('icons'), and mentions the platform ('The Noun Project'). However, it doesn't explicitly differentiate from sibling tools like 'search_collections' or 'icon_autocomplete', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'search_collections' or 'icon_autocomplete'. It mentions filtering capabilities but doesn't specify scenarios or prerequisites for usage, leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information about response format, whether it shows real-time vs cached data, rate limits of this tool itself, authentication requirements, or error conditions. 'Check' implies a read operation, but this isn't explicitly confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise at 7 words in a single sentence that directly states the tool's purpose. Every word earns its place with no redundancy or unnecessary elaboration. It's front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and zero parameters, the description is incomplete. While concise, it lacks crucial context about what information is returned (limits vs current usage, time periods, quota details), how frequently it should be called, or what the response structure looks like. The agent would need to invoke the tool blindly to understand its behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist. It earns a baseline 4 for not creating confusion about parameters that don't exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('check') and resources ('API usage limits and current usage'). It distinguishes from siblings like 'download_icon' or 'search_collections' by focusing on system monitoring rather than icon/collection operations. However, it doesn't explicitly differentiate from potential non-existent siblings in the usage monitoring domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, timing considerations, or comparison with other tools for monitoring API usage. The agent must infer usage context solely from the purpose statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information, implying a read-only operation, but doesn't address potential rate limits, authentication needs, error handling, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get detailed information about a specific icon') and lists key details (metadata, creator, tags, download URLs) without unnecessary words. Every element earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and key output aspects, but lacks behavioral details like rate limits or error handling, and doesn't explain return values since no output schema exists. This meets minimum viability but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for 'icon_id' and 'thumbnail_size' (including enum values). The description adds minimal value beyond the schema, mentioning 'detailed information' but not elaborating on how parameters affect the output. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'detailed information about a specific icon', specifying metadata, creator, tags, and download URLs. It distinguishes from siblings like 'download_icon' (which likely downloads files) and 'search_icons' (which searches multiple icons), but doesn't explicitly name alternatives or differentiate beyond the scope of a single icon.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving metadata of a specific icon, suggesting it's for detailed lookup rather than searching or downloading. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'search_icons' for broader queries or 'download_icon' for file retrieval, leaving usage context somewhat inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses format support (SVG/PNG) and API limitations (public domain only for free access), which are useful behavioral traits. However, it lacks details on permissions, rate limits, or error handling, leaving gaps for a mutation-like download operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by key features and a critical note, all in three concise sentences with zero wasted words. Each sentence adds distinct value, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no annotations, and no output schema, the description is moderately complete. It covers purpose, formats, and API limitations, but lacks details on return values, error cases, or authentication needs, which are important given the download operation's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds minimal value beyond the schema by mentioning 'custom color and size options' and format support, but doesn't provide additional syntax or constraints. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'download' and resource 'icon' with custom options, making the purpose evident. It distinguishes from siblings like 'get_icon' by specifying download functionality. However, it doesn't explicitly contrast with all siblings, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage through the mention of 'custom color and size options' and format support, but provides no explicit guidance on when to use this tool versus alternatives like 'get_icon' or 'search_icons'. The note about free API limitations offers some context but not sibling differentiation.
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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