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RJTechRamjee

ABAP Transport Analyzer MCP Server

by RJTechRamjee
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TypeScript
Remote

Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools are clearly distinct: one retrieves metadata (description, owner, status, objects), the other performs deep change analysis (diffs, risk factors). There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow the same verb_noun pattern: get_transport_metadata and analyze_transport_changes. The verbs are specific and consistent, making the naming predictable and readable.

    Tool Count3/5

    With only 2 tools, the server feels slightly thin. While each tool is meaningful and covers a distinct aspect of transport analysis, the count is at the low end of what is typically expected for a tool server.

    Completeness5/5

    For the stated purpose of analyzing ABAP transports, the two tools cover the full workflow: retrieving metadata and performing detailed change analysis with risk detection. There are no obvious gaps for this narrow domain.

  • 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
    • 2 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

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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?

    With no annotations, the description carries the transparency burden. It uses 'Retrieves' to imply read-only behavior and enumerates the returned data, which is useful. However, it does not disclose potential side effects, authorization needs, rate limits, or edge cases, and the 'Implements FR-1 requirements' line adds no behavioral insight.

    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 two sentences and front-loaded with the primary purpose. The first sentence is direct and informative. The second sentence ('Implements FR-1 requirements') is peripheral project context but does not materially bloat the description.

    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 tool has low schema complexity and no output schema, so the description partially compensates by listing return content. However, it does not explain how it differs from the sibling tool, and the absence of any usage guidance leaves a notable completeness gap.

    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 already provides full documentation for the single parameter (transportId) with a format example (DEVK900123). Since schema description coverage is 100%, the description adds no additional parameter semantics, matching the baseline score.

    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 'Retrieves transport request metadata' and lists specific data items (description, owner, status, complete list of modified objects). It identifies a specific verb and resource, but does not explicitly differentiate from the sibling tool 'analyze_transport_changes', which could also involve modified objects.

    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 the sibling tool. The description does not include any exclusions, prerequisites, or alternative recommendations, leaving the agent without clear selection criteria.

    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?

    There are no annotations, so the description must fully disclose behavior. It does state that the tool generates diffs, detects risk factors, and provides structured analysis, which are key behaviors. However, it doesn't explicitly state whether the tool is read-only or if any prerequisites exist, or what the exact output format is beyond 'structured analysis', leaving some ambiguity.

    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 two sentences and front-loaded with the primary action. The first sentence is dense but packs the main details, while the second sentence about FR-2/FR-3 is extra context that adds traceability but is not essential; overall it is efficient.

    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?

    With no output schema and no annotations, the description does a good job of describing what the tool does and what it returns (diffs, risk factors, structured analysis). It lacks some specifics like one might expect, but for a single-parameter tool, the coverage is quite thorough.

    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 schema fully describes the single parameter transportId with an example format (e.g., DEVK900123), achieving 100% schema coverage. The description does not add any additional parameter semantics, so the baseline score 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 uses the specific verb 'Performs' and identifies the resource as 'transport changes', then details the exact analyses performed (unified diffs, risk factors, structured analysis). This clearly distinguishes it from the sibling tool get_transport_metadata, which likely only fetches metadata.

    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 clearly states that the tool performs 'detailed analysis' and lists specific outputs, implying it should be used when deep analysis is needed. It doesn't explicitly mention when to use the sibling tool, but the contrast with get_transport_metadata is clear from the name and the 'detailed analysis' phrasing, providing clear context without exclusions.

    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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