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ygrec-app

SF Symbols MCP

by ygrec-app

Server Quality Checklist

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

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: exporting SVGs, getting symbol info, listing all symbols, and searching by keyword. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with underscores (export_symbol, get_symbol_info, list_symbols, search_symbols), making them predictable and easy to understand.

    Tool Count5/5

    With 4 tools, the server covers the essential operations for SF Symbols: listing, searching, retrieving details, and exporting. The count is appropriate for the domain.

    Completeness4/5

    The tool set covers querying (list/search/info) and exporting (SVG) adequately. A minor gap could be the lack of a 'preview' tool, but export serves that need. Overall, no critical missing operations for typical use.

  • Average 4/5 across 4 of 4 tools scored.

    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 MIT License.

  • This repository includes a README.md file.

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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?

    No annotations exist, so the description carries the full burden. It discloses that the tool returns JSON with total count and symbol names, and mentions the limit parameter. However, it does not discuss side effects, authentication needs, or whether it is purely read-only (though implied).

    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?

    Description is extremely concise: one sentence for purpose, one for parameters, one for returns. No unnecessary words, all information front-loaded. Every sentence adds value.

    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?

    The description provides the purpose, parameter, and return format, which is adequate for a simple tool with an output schema. However, it lacks guidance on when to use it versus siblings, and does not discuss error handling or edge cases.

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

    Parameters4/5

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

    Schema coverage is 0%, but the description adds meaningful context for the only parameter: 'limit: Maximum number of symbols to return (default 100)'. This clarifies the parameter's purpose and default, adding value beyond the schema's type and default.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description states 'List available SF Symbol names' which is a specific verb and resource. It clearly distinguishes from siblings like search_symbols (which searches) and get_symbol_info (which gets details for a specific symbol) by focusing on listing all available names.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance provided on when to use this tool versus alternatives like search_symbols or get_symbol_info. The description does not mention use cases or exclusions, leaving the agent to infer context.

    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 exist, so the description must carry the behavioral disclosure burden. It only states the return format (JSON with availability, related symbols, renderability) but omits any behavioral traits such as read-only nature, authorization needs, rate limits, or error conditions. For a read operation, the description is insufficiently transparent.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

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

    The description is extremely concise with no wasted words. It is logically structured: a one-line summary followed by Args and Returns sections. Every sentence adds value.

    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 (one parameter, read operation) and the presence of an output schema, the description is largely sufficient. It covers what the tool does and its return structure. Missing elements like error handling or preconditions are minor for this context.

    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% description coverage, but the tool description adds meaningful context: it defines the parameter as 'Exact SF Symbol name' and provides concrete examples (e.g., 'star.fill'). This goes beyond the minimal schema and compensates for the lack of schema descriptions, though it could include validation constraints.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states it retrieves information about a specific SF Symbol, with a clear verb ('Get') and resource ('information about a specific SF Symbol'). It naturally distinguishes from sibling tools like list_symbols (listing many) and search_symbols (searching) by focusing on a single symbol.

    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 when you have a specific symbol name, but provides no explicit guidance on when to prefer this tool over siblings or when not to use it. Sibling names are provided but not discussed.

    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 full burden. It states it returns matching names and count but does not disclose critical behavioral traits such as case sensitivity, fuzzy vs exact matching, result limits, or whether it searches only names or also descriptions. These gaps hinder an agent's ability to predict search behavior.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

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

    The description is extremely concise: two sentences and a structured args/returns block. Every sentence adds value, and the purpose is front-loaded. 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?

    For a simple search tool with one parameter and an existing output schema, the description covers the core purpose and return type. It could mention search behavior details (exact vs fuzzy) but is largely complete for its complexity.

    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 single 'query' parameter has 0% schema description coverage, so the description compensates by providing concrete examples ('star', 'circle', etc.), which adds meaningful usage guidance beyond the schema title.

    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 for SF Symbol names by name or keyword, which is a specific verb and resource. The sibling tools (export_symbol, get_symbol_info, list_symbols) have distinct purposes, so this tool is well-differentiated.

    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 for finding symbols by keyword but does not explicitly state when to use this tool versus alternatives like list_symbols or get_symbol_info. No exclusions or prerequisites are mentioned.

    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?

    No annotations are provided, so the description carries the full burden. It explains the output format (SVG content or file save), coordinate system options (raw_coords), and default behavior. However, it could explicitly state non-destructive nature or auth requirements. Still, it adds significant behavioral context beyond the schema.

    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 well-structured with an Args section and Returns section. Each parameter is documented concisely without unnecessary repetition. The overall length is appropriate for the tool's complexity.

    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?

    Given the tool has an output schema (not shown but present), the description need not detail return values further. It covers all 5 parameters, default values, and edge cases like raw_coords. The description is sufficient for an agent to correctly invoke the tool.

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

    Parameters5/5

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

    The schema has 0% description coverage, so the description must explain each parameter. It does thoroughly: name, weight (with list of valid values), size (with default), output_path (with behavior if not provided), raw_coords (with explanation of coordinate system). This adds essential meaning beyond the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool exports an SF Symbol as SVG with vector paths, using a specific verb and resource. The sibling tools are about information retrieval (get_symbol_info, list_symbols, search_symbols), so this tool is distinctly about export.

    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?

    While there is no explicit 'when to use' or 'when not to use', the purpose is clear and distinct from siblings. The description focuses on parameter details, but the context signals strongly imply this tool is for exporting SVGs, not for other symbol queries.

    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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