Skip to main content
Glama
xiaobenyang-com

Iconify-Icon

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation4/5

    The tools have mostly distinct purposes: get_all_icon_sets lists collections, get_icon_data fetches a specific icon, get_icon_set retrieves all icons in a set, and search_icons finds icons via queries. There is some potential overlap between get_icon_set and search_icons when searching within a specific set, but the descriptions clarify their primary focuses, making misselection unlikely.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case: get_all_icon_sets, get_icon_data, get_icon_set, and search_icons. The verbs 'get' and 'search' are appropriately used and predictable, with no deviations in style or convention.

    Tool Count5/5

    With 4 tools, the server is well-scoped for its purpose of icon retrieval and browsing. Each tool serves a clear, non-redundant function, covering key operations like listing sets, fetching specific data, and searching, without being overly sparse or bloated.

    Completeness4/5

    The tool surface covers core CRUD-like operations for icon data retrieval: browsing, fetching specific icons, exploring sets, and searching. A minor gap exists in lacking direct update or delete tools, but this is reasonable for a read-only icon library, and agents can work effectively with the provided tools for typical use cases.

  • Average 3.5/5 across 4 of 4 tools scored. Lowest: 2.9/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 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 Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'returns matching icons,' which indicates a read operation, but lacks details on permissions, rate limits, pagination, or response format. The description is minimal and doesn't compensate for the absence of 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 two sentences that are front-loaded and to the point. Each sentence adds value: the first defines the action and resource, the second clarifies the scope. There's no wasted verbiage, though it could be slightly more informative.

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

    Completeness2/5

    Given 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 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or parameter usage, leaving significant gaps for an AI agent to understand how to invoke it correctly.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'flexible query parameters' but doesn't explain the semantics of query, prefix, or limit. The description adds no meaningful information beyond what the bare schema provides, failing to address the coverage gap.

    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's purpose: 'Search through Iconify's icon collection with flexible query parameters.' It specifies the action (search), resource (Iconify's icon collection), and scope (all icon sets or specific set). However, it doesn't explicitly differentiate from sibling tools like get_all_icon_sets or get_icon_set, which appear to be retrieval rather than search operations.

    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 implies usage context by mentioning 'flexible query parameters' and the ability to search 'all icon sets or a specific set,' but doesn't provide explicit guidance on when to use this tool versus alternatives like get_icon_data or get_icon_set. No when-not-to-use scenarios or prerequisite information is included.

    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 mentions that the tool retrieves data and provides usage examples, which is helpful. However, it doesn't address important behavioral aspects like whether this is a read-only operation, what format the returned data takes (e.g., JSON, SVG code), whether there are rate limits, or if authentication is required. For a tool with no annotation coverage, this leaves significant gaps.

    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 efficiently structured in two sentences: the first states the purpose and scope, the second provides critical parameter format details with examples. Every sentence earns its place with no wasted words, making it easy to parse and front-loaded with essential information.

    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?

    Given the tool's moderate complexity (1 parameter, no output schema, no annotations), the description is partially complete. It covers the purpose and parameter format well, but lacks details on return values (since no output schema exists), behavioral constraints, and differentiation from sibling tools. This makes it adequate but with clear gaps for effective agent use.

    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 has 1 parameter with 0% description coverage, so the description must compensate. It provides clear semantics for the 'icon' parameter: it must be 'the full icon name in format 'prefix:icon-name'' with examples ('mdi:home', 'fa:user'). This adds substantial value beyond the bare schema, though it doesn't explain what prefixes are valid or where to find them.

    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's purpose: 'Retrieve specific icon data with usage examples for popular frameworks'. It specifies the verb ('Retrieve'), resource ('icon data'), and scope ('usage examples for popular frameworks'). However, it doesn't explicitly distinguish this from sibling tools like 'get_icon_set' or 'search_icons', which likely retrieve different types of icon information.

    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 some implied usage guidance by specifying the required input format ('Provide the full icon name in format 'prefix:icon-name'') and mentioning frameworks. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_icons' or 'get_icon_set', nor does it mention any prerequisites or exclusions.

    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. It states the tool retrieves information, implying a read-only operation, but does not disclose behavioral traits such as error handling (e.g., what happens if an invalid prefix is provided), rate limits, authentication needs, or the format of the returned data. 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is appropriately sized with two sentences: the first states the purpose and scope, and the second provides parameter guidance. Each sentence earns its place by adding value without redundancy, making it front-loaded and efficient.

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

    Completeness2/5

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

    Given the tool has no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It covers the basic purpose and parameter meaning but lacks critical context such as return value format, error conditions, or behavioral details needed for effective use. This is inadequate for a tool with one parameter and no structured support.

    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?

    The input schema has 0% description coverage, with one parameter 'prefix' undocumented in the schema. The description adds meaning by explaining that 'prefix' refers to 'the icon set prefix (e.g., 'mdi', 'fa', 'bi')', providing essential semantics. However, it does not fully compensate for the coverage gap, as it lacks details on constraints (e.g., valid prefixes, case sensitivity) or examples beyond the listed ones.

    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 verb 'Retrieve' and the resource 'detailed information about a specific icon set including all available icons in that set', making the purpose specific. It distinguishes from sibling tools like 'get_all_icon_sets' (which retrieves multiple sets) and 'search_icons' (which searches across icons), establishing clear differentiation.

    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 context by specifying 'Provide the icon set prefix (e.g., 'mdi', 'fa', 'bi')', which indicates when to use this tool (for a specific icon set). However, it does not explicitly state when not to use it or name alternatives like 'get_all_icon_sets' for broader retrieval, missing full explicit guidance.

    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 the tool returns a list with metadata fields (name, total icons, author, license, sample icons), which is useful behavioral context. However, it doesn't mention pagination, rate limits, authentication needs, or error conditions that would be important for a tool returning 200+ sets.

    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 efficiently structured in two sentences: first establishes purpose and scope, second details return format. Every element earns its place with no redundant information. The front-loaded mention of 'Browse all available icon collections' immediately communicates the core function.

    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?

    Given no annotations and no output schema, the description provides adequate basic information about what the tool does and returns. However, for a tool that presumably returns a substantial dataset (200+ sets), more context about response format, pagination, or performance considerations would be helpful. The description is complete enough for basic use but lacks depth for robust implementation.

    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 input schema has 0 parameters with 100% coverage, so the schema already fully documents the lack of parameters. The description appropriately doesn't add parameter information beyond what the schema provides, maintaining a clean baseline. A score of 4 reflects that the description doesn't need to compensate for any parameter gaps.

    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 specific action ('Browse all available icon collections'), identifies the resource ('Iconify icon sets'), and distinguishes from siblings by specifying it returns 'all' icon sets rather than filtering or searching like get_icon_set or search_icons. The mention of '200+ icon sets with 200,000+ icons' provides concrete 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 implies usage context by stating it returns 'all available icon collections' and listing metadata fields, suggesting this is for browsing complete catalog. However, it doesn't explicitly state when to use this vs. alternatives like get_icon_set (for specific set) or search_icons (for filtered search), though the 'all' wording provides some differentiation.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

1777316659568643 MCP server

Copy to your README.md:

Score Badge

1777316659568643 MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

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

curl -X GET 'https://glama.ai/api/mcp/v1/servers/xiaobenyang-com/1777316659568643'

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