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andreimaxim

papertrail-mcp

by andreimaxim
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TypeScript
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have entirely distinct purposes: one lists configured credential environments, the other executes a generic GET request to the Papertrail API. There is no overlap or confusion between them.

    Naming Consistency4/5

    Both tools use snake_case and are prefixed with 'papertrail_', but one follows a verb_noun pattern (list_environments) while the other is a bare verb (get). This is mostly consistent but not perfectly uniform.

    Tool Count3/5

    With only two tools, the server is at the low end of the acceptable range. For its narrow read-only purpose, the minimal set is understandable, but it still feels thin compared to typical MCP servers.

    Completeness4/5

    The tool pair covers the essential workflow of identifying an environment and making an authenticated GET request, which is sufficient for basic read-only access. However, there is no dedicated search or pagination tool, though agents can work around this via the generic GET.

  • Average 3.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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

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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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Annotations already declare read-only and idempotent behavior. The description adds the valuable guarantee that API tokens and URLs are not exposed, which is a behavioral trait beyond what the annotations convey.

    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 a single, concise sentence that is front-loaded with the action and includes no unnecessary words. It communicates the essential behavior clearly.

    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 list tool with no parameters and no output schema, the description covers the core behavior and the safety guarantee. It does not explicit mention the return format, but that is implied by the act of listing environment names.

    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 tool has zero parameters, so schema coverage is effectively 100%. The description correctly omits parameter details, and the baseline score of 4 applies for the zero-parameter case.

    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 lists configured Papertrail credential environments and specifically mentions the non-exposure of API tokens or URLs. It does not explicitly distinguish from the sibling papertrail_get, but the verb 'list' versus 'get' conveys a different scope.

    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 is provided on when to use this tool versus papertrail_get. The description is purely a statement of function, with no mention of use cases, exclusions, or alternatives.

    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?

    Annotations already declare readOnly, idempotent, and non-destructive behavior, but the description adds valuable context beyond that: it requires authentication, performs a single GET request, and cautions that large output may be truncated. This goes beyond the structured annotations and helps set expectations for API 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 two sentences, front-loaded with the core action and resource, and each sentence provides essential information without wasted words. Truncation warning and read-only note are succinctly included.

    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 simple GET nature of the tool, the description is reasonably complete: it covers the action, endpoint, auth, read-only safety, and truncation risk. The lack of an output schema is partially mitigated by the 'logs' focus, but a brief note about the response format would make it fully complete.

    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%, and the parameter descriptions clearly explain 'path', 'query', and 'environment' including the note about pageInfo.nextPage. The main tool description adds no additional parameter semantics, so the baseline of 3 applies.

    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 ('Make one authenticated GET request') and the specific resource ('migrated Papertrail logs API at /v1/logs'), making it obvious this tool fetches logs. It also notes that it is read-only, which aligns with the annotations and helps differentiate it from the sibling environment-listing tool.

    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 does not explicitly state when to use this tool versus the sibling tool papertrail_list_environments. However, the tool name and resource path imply its purpose, and the environment parameter description mentions using list_environments to discover values, providing limited indirect guidance. Usage is implied but not formally articulated.

    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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