Noun Project MCP Server
Enables searching and retrieving icons from The Noun Project, with support for advanced filtering by style and line weight, collection management, search autocomplete, usage tracking, and generating customized download URLs with color and size options.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Noun Project MCP Serversearch for a red line icon of a house"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Noun Project MCP Server
A Model Context Protocol (MCP) server for The Noun Project API, enabling Claude Code to search and retrieve icons programmatically.
Features
Icon Search: Search for icons with advanced filters (style, line weight, public domain)
Icon Details: Get detailed information about specific icons
Collections: Retrieve icon collections
Autocomplete: Get search term suggestions
Usage Tracking: Monitor API quota and usage
Download URLs: Get customized download links with color and size options
Related MCP server: iconfont-mcp
Prerequisites
Node.js: Version 18 or higher
Noun Project API Credentials: Get your API key and secret from The Noun Project
Installation
Quick Install (Recommended)
Install directly from npm and add to Claude Code in one command:
claude mcp add --transport stdio noun-project \
--env NOUN_PROJECT_API_KEY=your_api_key_here \
--env NOUN_PROJECT_API_SECRET=your_api_secret_here \
-- npx -y noun-project-mcpReplace your_api_key_here and your_api_secret_here with your actual credentials from The Noun Project.
Local Development
Clone and navigate to the repository:
git clone https://github.com/sgup/noun-project-mcp.git
cd noun-project-mcpInstall dependencies:
npm installBuild the TypeScript code:
npm run buildAdd to Claude Code using local path:
claude mcp add --transport stdio noun-project \
--env NOUN_PROJECT_API_KEY=your_api_key_here \
--env NOUN_PROJECT_API_SECRET=your_api_secret_here \
-- node /absolute/path/to/noun-project-mcp/dist/index.jsAvailable Tools
1. search_icons
Search for icons with various filters.
Parameters:
query(required): Search term (e.g., "dog", "house")styles(optional): Filter by style - "solid", "line", or "solid,line"line_weight(optional): For line icons, specify weight (1-60) or range (e.g., "18-20")limit_to_public_domain(optional): Set to 1 for public domain onlythumbnail_size(optional): 42, 84, or 200 pixelsinclude_svg(optional): Set to 1 to include SVG URLslimit(optional): Maximum number of results
Example:
{
"query": "dog",
"styles": "line",
"limit": 10
}2. get_icon
Get detailed information about a specific icon.
Parameters:
icon_id(required): The icon's unique IDthumbnail_size(optional): 42, 84, or 200 pixels
Example:
{
"icon_id": 12345,
"thumbnail_size": 200
}3. get_collection
Retrieve a collection and its icons.
Parameters:
collection_id(required): The collection's unique IDthumbnail_size(optional): 42, 84, or 200 pixelsinclude_svg(optional): Set to 1 to include SVG URLslimit(optional): Maximum number of icons to return
Example:
{
"collection_id": 123
}4. icon_autocomplete
Get autocomplete suggestions for search terms.
Parameters:
query(required): Partial search termlimit(optional): Maximum number of suggestions
Example:
{
"query": "hom",
"limit": 5
}5. check_usage
Check current API usage and limits.
Parameters: None
6. get_download_url
Get a download URL for an icon with customization.
Parameters:
icon_id(required): The icon's unique IDcolor(optional): Hexadecimal color (e.g., "FF0000")filetype(optional): "svg" or "png"size(optional): For PNG, size in pixels (20-1200)
Example:
{
"icon_id": 12345,
"color": "FF0000",
"filetype": "png",
"size": 512
}Development
Run in development mode with auto-rebuild:
npm run devBuild for production:
npm run buildStart the server:
npm startAPI Reference
This MCP server uses The Noun Project API v2. For more details about the API:
Authentication
The Noun Project API uses OAuth 1.0 authentication. This server handles all OAuth signing automatically using your API credentials.
Usage Limits
The Noun Project API has monthly usage limits. Use the check_usage tool to monitor your quota.
Troubleshooting
"NOUN_PROJECT_API_KEY and NOUN_PROJECT_API_SECRET must be set"
Make sure you included the --env flags when running claude mcp add. You can verify your configuration with:
claude mcp listTo update your credentials, remove and re-add the server:
claude mcp remove noun-project
claude mcp add --transport stdio noun-project \
--env NOUN_PROJECT_API_KEY=your_new_key \
--env NOUN_PROJECT_API_SECRET=your_new_secret \
-- npx -y noun-project-mcp"Invalid signature" errors
Verify that your API key and secret are correct and haven't been regenerated in The Noun Project dashboard.
Connection issues
Ensure you have an active internet connection and that The Noun Project API is accessible.
License
MIT
Support
For issues with this MCP server, please file an issue on the repository.
For issues with The Noun Project API, visit their support page.
Available Tools
7 toolscheck_usageB
Check current API usage and limits. Returns monthly quota information including usage count and remaining requests.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 this is a read operation ('Check', 'Returns') and specifies the type of information returned ('monthly quota information including usage count and remaining requests'). However, it doesn't mention important behavioral aspects like whether this counts against rate limits itself, authentication requirements, or error conditions. The description adds some value but leaves gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise and well-structured: two sentences that each earn their place. The first states the purpose, the second specifies the return information. No wasted words, no redundancy, and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is reasonably complete for a basic read operation. It explains what information is returned, which compensates for the lack of output schema. However, for a usage/limits tool, it could benefit from mentioning typical use cases (monitoring, planning requests) or behavioral constraints. The description is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 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 focuses instead on what the tool returns, which is valuable context. This earns a baseline 4 for zero-parameter tools that don't mislead about parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check current API usage and limits' specifies the verb ('Check') and resource ('API usage and limits'), and 'Returns monthly quota information...' adds detail about what information is provided. However, it doesn't differentiate this from potential sibling tools (none listed are usage/limit tools), so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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, frequency of use, or contextual triggers. While there are no obvious sibling alternatives for usage checking, the description lacks any usage context beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_collectionC
Get a collection by ID. Returns collection metadata and the icons it contains.
| Name | Required | Description | Default |
|---|---|---|---|
| collection_id | Yes | The unique ID of the collection | |
| thumbnail_size | No | Thumbnail size to return for icons (42, 84, or 200 pixels) | |
| include_svg | No | Set to 1 to include SVG URLs in the response | |
| limit | No | Maximum number of icons to return from the collection |
TDQS
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 mentions the return content but lacks details on permissions, rate limits, error handling, or whether it's a read-only operation. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, consisting of two concise sentences that directly state the tool's purpose and return value without any unnecessary information. Every sentence earns its place by providing essential context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return format beyond high-level mentions, leaving gaps in understanding how to interpret results like metadata structure or icon data, which is inadequate for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter semantics beyond what the input schema provides, which has 100% coverage with clear descriptions for all parameters. The baseline is 3 when the schema does the heavy lifting, as the description doesn't compensate with additional context like default values or usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does 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 ('collection by ID'), and mentions what it returns ('collection metadata and the icons it contains'). However, it doesn't explicitly distinguish this tool from its siblings like 'search_collections' or 'get_icon', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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 'get_collection' over 'search_collections' for finding collections or 'get_icon' for individual icons, nor does it discuss prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_download_urlB
Get a download URL for an icon with custom color and size options. Supports SVG and PNG formats. Note: Free API access is limited to public domain icons only.
| Name | Required | Description | Default |
|---|---|---|---|
| icon_id | Yes | The unique ID of the icon to download | |
| color | No | Hexadecimal color value (e.g., "FF0000" for red) | |
| filetype | No | File format: svg or png (note: SVG does not accept size parameter) | |
| size | No | For PNG only, size in pixels (minimum 20, maximum 1200) |
TDQS
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 adds useful context: the tool is for downloading icons with customization, supports specific formats, and has a free API limitation. However, it lacks details on rate limits, authentication needs, error handling, or what the download URL entails (e.g., expiration, access controls). For a tool with no annotations, this is a moderate but incomplete disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds important context (formats and API limitation). Both sentences earn their place by providing essential information without redundancy. It could be slightly more structured by explicitly separating usage notes, but it remains efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides basic context but has gaps. It covers the tool's purpose, formats, and a free API limitation, but lacks details on behavioral aspects like rate limits, authentication, or what the output (download URL) entails. For a tool with 4 parameters and no structured output information, this is a minimal viable description, leaving the agent to infer or handle unknowns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 parameters thoroughly. The description adds minimal value beyond the schema: it mentions 'custom color and size options' and 'Supports SVG and PNG formats,' which are already covered in the schema's descriptions and enum. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description does not significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 a download URL for an icon with custom color and size options. Supports SVG and PNG formats.' It specifies the verb ('Get'), resource ('download URL for an icon'), and key features (color, size, formats). However, it does not explicitly differentiate from sibling tools like 'get_icon' or 'search_icons', which might offer overlapping functionality, so it falls short of 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some implied usage context: it mentions 'Free API access is limited to public domain icons only,' which hints at when to use it (for public domain icons) and potential limitations. However, it does not explicitly state when to use this tool versus alternatives like 'get_icon' or 'search_icons,' nor does it provide clear exclusions or prerequisites beyond the free API note. This leaves gaps in guidance for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_iconC
Get detailed information about a specific icon by its ID. Returns icon metadata, creator info, tags, and download URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| icon_id | Yes | The unique ID of the icon | |
| thumbnail_size | No | Thumbnail size to return (42, 84, or 200 pixels) |
TDQS
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 mentions the return content ('metadata, creator info, tags, and download URLs') but doesn't cover critical aspects like authentication needs, rate limits, error handling, or whether it's a read-only operation. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with the core purpose stated first and return details added efficiently. Both sentences earn their place by clarifying the action and output. It could be slightly improved by integrating usage context, but it avoids waste and is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given 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 minimally adequate. It covers the purpose and return values but lacks behavioral details and usage guidelines. Without annotations or output schema, it should do more to compensate, but it's not entirely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 both parameters ('icon_id' and 'thumbnail_size') with descriptions and enum values. The description adds no additional parameter semantics beyond what the schema provides, such as format details or usage examples. 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.
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 detailed information about a specific icon by its ID.' It specifies the verb ('Get'), resource ('icon'), and identifier method ('by its ID'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_collection' or 'search_icons', 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.
Does 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 sibling tools like 'get_collection' for collection-level data or 'search_icons' for broader queries, nor does it specify prerequisites or exclusions. Usage is implied only by the purpose statement, lacking explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
icon_autocompleteB
Get autocomplete suggestions for icon search terms. Useful for helping users discover related terms.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Partial search term to get suggestions for | |
| limit | No | Maximum number of suggestions to return |
TDQS
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 mentions the tool provides 'suggestions' and is 'useful for helping users discover related terms,' which implies a read-only, non-destructive operation. However, it doesn't disclose key behavioral traits such as rate limits, authentication needs, response format, or error handling, which are important for an agent to use it correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of two sentences that directly state the tool's purpose and utility. There's no unnecessary information or repetition, making it efficient. However, it could be slightly improved by integrating usage guidance more seamlessly, but overall it's well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given 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 somewhat complete but has gaps. It covers the basic purpose and utility, but without annotations or an output schema, it lacks details on behavioral traits and return values, which could hinder an agent's ability to use it effectively in all contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does 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 both parameters ('query' and 'limit'), so the schema does the heavy lifting. The description doesn't add any meaningful parameter semantics beyond what's in the schema, such as examples or constraints, but it doesn't need to compensate for gaps, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does 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 autocomplete suggestions') and resource ('icon search terms'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate this from sibling tools like 'search_icons' or 'get_icon', which might offer similar search-related functionality, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance by stating it's 'useful for helping users discover related terms,' suggesting it should be used for search assistance. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_icons' or 'get_icon,' and doesn't specify any exclusions or prerequisites, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_collectionsC
Search for collections on The Noun Project. Returns a list of collections matching the search term.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search term for collections (e.g., "winter", "business", "animals") | |
| blacklist | No | Set to 1 to remove results matching terms or IDs in blacklist | |
| limit | No | Maximum number of results to return | |
| prev_page | No | Token for paging to the previous page | |
| next_page | No | Token for paging to the next page |
TDQS
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 the return type ('list of collections') but lacks details on permissions, rate limits, pagination behavior (implied by parameters but not explained), or error handling. This is a significant gap 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that efficiently convey the tool's purpose and outcome. It's front-loaded with the main action and avoids unnecessary details, though it could be slightly more structured by explicitly mentioning key parameters like pagination.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the behavioral aspects (e.g., how pagination works with 'prev_page' and 'next_page'), return format details, or error cases, leaving gaps for the agent to navigate this search tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does 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 search functionality, which is already clear from the schema. This meets the baseline of 3 for high schema coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does 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 resource ('on The Noun Project'), with the outcome ('Returns a list of collections matching the search term'). It distinguishes from siblings like 'search_icons' by specifying collections, but doesn't explicitly contrast with 'get_collection' or others, 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'search_icons' or 'get_collection'. The description only states what it does, not when it's appropriate, leaving the agent to infer usage from context without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_iconsC
Search for icons on The Noun Project. Supports filtering by style (solid/line), line weight, public domain status, and more.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search term for icons (e.g., "dog", "house", "bicycle") | |
| styles | No | Filter by icon style: solid, line, or both (solid,line) | |
| line_weight | No | For line icons, filter by line weight (1-60) or range (e.g., "18-20") | |
| limit_to_public_domain | No | Set to 1 to limit results to public domain icons only | |
| thumbnail_size | No | Thumbnail size to return (42, 84, or 200 pixels) | |
| include_svg | No | Set to 1 to include SVG URLs in the response | |
| limit | No | Maximum number of results to return |
TDQS
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. While it mentions filtering capabilities, it doesn't describe important behavioral aspects like rate limits, authentication requirements, pagination behavior, error conditions, or what the response format looks like. For a search tool with 7 parameters, this leaves significant gaps in understanding how the tool actually behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in a single sentence that front-loads the core purpose. It wastes no words while covering the main filtering capabilities. However, it could be slightly more structured by separating the core purpose from the filtering features.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 7 parameters and no output schema, the description is incomplete. It doesn't explain what the tool returns (icon metadata, thumbnails, download URLs), how results are structured, or important behavioral constraints. Without annotations or output schema, users lack crucial information about what to expect from this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions filtering by style, line weight, and public domain status, which maps to some parameters. However, with 100% schema description coverage, the input schema already provides comprehensive parameter documentation. The description adds minimal value beyond what's already in the structured schema, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search for icons') and the resource ('on The Noun Project'), which provides specific verb+resource pairing. However, it doesn't explicitly differentiate this tool from sibling tools like 'icon_autocomplete' or 'get_icon', which might also involve icon retrieval operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions filtering capabilities but provides no guidance on when to use this tool versus alternatives like 'icon_autocomplete' or 'get_icon'. There's no indication of prerequisites, typical use cases, or when other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
v1.0.0- Changed
get_download_url2 fields changed- changed
Input schema / properties / filetype / descriptionPrevious value: -"File format: svg or png"New value: +"File format: svg or png (note: SVG does not accept size parameter)" - changed
Input schema / properties / size / descriptionPrevious value: -"For PNG, size in pixels (minimum 20, maximum 1200)"New value: +"For PNG only, size in pixels (minimum 20, maximum 1200)"
- Added
search_collections
6 tool updates
- First observed
check_usage - First observed
get_collection - First observed
get_download_url - First observed
get_icon - First observed
icon_autocomplete - First observed
search_icons
TDQS
Each tool has a clearly distinct purpose with no ambiguity. Tools like 'check_usage' (API monitoring), 'get_collection' (collection retrieval), 'get_download_url' (icon download configuration), 'get_icon' (icon metadata), 'icon_autocomplete' (search suggestions), 'search_collections' (collection search), and 'search_icons' (icon search) target specific, non-overlapping operations in the Noun Project domain.
All tool names follow a consistent verb_noun pattern using snake_case throughout. Examples include 'check_usage', 'get_collection', 'search_icons', and 'icon_autocomplete', with verbs like 'check', 'get', and 'search' applied predictably to relevant nouns, making the set highly readable and systematic.
With 7 tools, this server is well-scoped for its purpose of interacting with The Noun Project API. Each tool earns its place by covering essential operations such as usage checking, collection and icon retrieval, search, and download management, without being overly sparse or bloated for the domain.
The tool surface provides strong coverage for core Noun Project workflows, including search, retrieval, and download of icons and collections, plus API usage monitoring. A minor gap exists in CRUD operations for user-specific resources like managing personal collections or favorites, but agents can effectively work around this for most use cases.
Maintenance
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