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User0856

snaprender-mcp

by User0856
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JavaScript
Hybrid

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.5.4

  • Disambiguation5/5

    Each tool has a distinct purpose: checking cache, retrieving usage stats, and capturing screenshots. There is no overlap in functionality.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case, making the set predictable and easy to understand.

    Tool Count5/5

    Three tools is an appropriate size for a focused screenshot service, covering essential operations without unnecessary complexity.

    Completeness4/5

    The tool set covers the core workflow of capturing screenshots, with supplementary tools for cache checking and usage tracking. A minor gap is the absence of cache management operations.

  • Average 4/5 across 3 of 3 tools scored.

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • 2 commits in the last 12 weeks
    • Last stable release on
    • 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.

  • 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.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

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

    Then . Browse examples.

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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 provided, so description carries full burden. It mentions output formats and features but lacks details on error behavior, rate limits, or prerequisites.

    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?

    Single sentence covering core action and key features. No fluff, front-loaded with main purpose.

    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?

    13 parameters, no output schema, no annotations. Description lists formats but does not specify how the result is returned (e.g., binary, URL). Could be more complete on output.

    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 coverage is 100%, baseline 3. Description adds overview of features but does not elaborate on parameter usage beyond what schema already provides.

    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 'Capture a screenshot of any website' with specific verb and resource. It lists many features like format support, device emulation, dark mode, etc., clearly distinguishing it from sibling tools (check_screenshot_cache, get_usage).

    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?

    No explicit guidance on when to use this vs alternatives. The sibling tools are about cache checking and usage, so the context is implied but not stated.

    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?

    No annotations provided; description indicates a read-only operation retrieving usage statistics. Discloses what data is returned but does not mention any side effects, authentication requirements, or rate limits. Adequate for a simple getter.

    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?

    Single sentence of 13 words, directly communicates purpose and included fields. No wasted words; perfectly concise.

    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 no parameters and no output schema, description adequately lists the three pieces of information returned (screenshots used, limit, remaining quota). Could specify data types or format, but minimally complete for a simple statistics endpoint.

    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?

    Input schema has zero parameters, so schema_description_coverage is 100%. Baseline for zero-parameter tools is 4; description adds no parameter info as none are needed.

    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 clearly states it retrieves current month's screenshot usage statistics with specific fields (screenshots used, limit, remaining quota). Differentiates from sibling tools (check_screenshot_cache, take_screenshot) which focus on capturing or caching screenshots.

    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?

    No explicit guidance on when to use this tool versus siblings. Usage is implied by the name and description, but lacks when-not-to-use or alternative recommendations. For a simple stats tool, this is minimally adequate.

    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?

    Despite no annotations, the description discloses a key behavioral trait: it does not count against quota. This is important for usage optimization. It does not mention return values or side effects, but the tool is simple and low-risk.

    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?

    Two sentences, zero wasted words. The description is front-loaded with the primary purpose and immediately adds a key differentiator (quota). Perfect conciseness.

    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 cache-check tool with no output schema and clear sibling context, the description is sufficient. It explains the core function and a critical behavioral note. Minor gap: does not describe the return format (e.g., boolean), but not essential for an agent to invoke 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?

    Input schema has 100% description coverage with basic descriptions for 'url' and 'format'. The description adds no additional insight beyond the schema, so it meets the baseline for schema-rich tools but does not enhance understanding.

    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 'check' and the resource 'screenshot cache'. It distinguishes from sibling 'take_screenshot' by noting it does not capture a new screenshot, and adds a unique benefit: not counting against quota. This is specific and helpful.

    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 the tool is for verifying cache before capturing, but does not explicitly state when to use vs. 'take_screenshot' or 'get_usage'. However, the sibling context and the phrase 'without capturing a new one' provide clear contextual guidance.

    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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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.

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