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splinesreticulating

Icecast MCP Server

by splinesreticulating
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one analyzes a specific configuration file, while the other provides general best practices. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow the same verb_noun pattern with descriptive prefixes (analyze_icecast_config, get_icecast_best_practices), maintaining full consistency.

    Tool Count3/5

    With only 2 tools, the server feels thin for its stated purpose. While the tools are focused, a broader scope (e.g., validation, editing) would justify more tools, but it's borderline acceptable.

    Completeness3/5

    The tools cover analysis and best practices, but lack validation, comparison, or modification capabilities. This leaves notable gaps for a comprehensive configuration tool.

  • Average 3.6/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • No commit activity data available
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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

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

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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 the full burden of disclosing behavioral traits. It only states the function is to 'get' recommendations, which implies a read-only operation, but does not detail any side effects, data source, or operational constraints. The description adds minimal value 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.

    Conciseness4/5

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

    The description is a single, concise sentence with no redundancy. It is front-loaded but very brief. While efficient, it could benefit from a slight expansion to include behavioral or usage context without sacrificing conciseness.

    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 has one parameter, no output schema, and no annotations, the description provides the minimum viable information. It explains what the tool does but does not specify the format or structure of the returned recommendations, leaving gaps for an agent to interpret correctly.

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

    Parameters3/5

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

    Schema description coverage is 100% with a detailed description for the 'useCase' parameter including enum values and listener ranges. The tool description ('based on use case') does not add meaning beyond the schema, so the baseline score of 3 is appropriate.

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

    Purpose5/5

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

    The description clearly states the action ('Get'), the resource ('general best practices and recommendations for Icecast configuration'), and the condition ('based on use case'). It effectively distinguishes from the sibling tool 'analyze_icecast_config', which implies a focus on specific config analysis versus general recommendations.

    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 obtaining best practices by use case but does not explicitly state when to use this tool versus its sibling or alternatives. No 'when not to use' guidance is provided, leaving the decision to the agent's inference.

    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 the full burden of behavioral disclosure. It states the tool analyzes and provides recommendations, but does not mention that it is read-only, what permissions might be needed, or any potential side effects. The description is adequate but lacks detail.

    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 consists of two concise sentences that immediately convey the primary action and scope. Every sentence adds value without redundancy.

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

    Completeness4/5

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

    Given the tool's simplicity (no output schema, two parameters) and lack of annotations, the description is fairly complete: it identifies the file type, the action, and the areas of analysis. However, it could be improved by specifying the output format or nature of recommendations.

    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 100% description coverage for both parameters, so the schema already explains their meaning. The tool description itself does not elaborate on the parameters, but given the schema coverage, it does not need to. Baseline score of 3 is appropriate.

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

    Purpose5/5

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

    The description clearly states the verb 'Analyze' and the resource 'Icecast XML configuration file', and specifies the areas of improvement (security, performance, capacity, reliability). This distinguishes it from the sibling tool 'get_icecast_best_practices', which likely provides general best practices rather than analyzing a specific file.

    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 that the tool should be used when you have a specific Icecast configuration file to analyze, but it does not explicitly state when to use it versus the sibling tool 'get_icecast_best_practices'. No guidance on prerequisites or when not to use it is provided.

    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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