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RaghavOfficialGit

MCP ABAP Server

by RaghavOfficialGit
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have distinct purposes: one discovers available object types and the other queries actual ABAP objects. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow the same verb_noun snake_case pattern (query_abap_objects, get_object_types), making the naming predictable and consistent.

    Tool Count3/5

    With only two tools, the server feels minimal but not absurdly so. It covers a basic query and type discovery flow, yet a broader ABAP server would likely need more tools.

    Completeness3/5

    The surface provides basic querying and type discovery, but lacks obvious operations like retrieving detailed object metadata or source code. It is a workable but minimal set for ABAP exploration.

  • Average 3.2/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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

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  • 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

  • Behavior2/5

    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 implies a read-only query but does not mention return shape, pagination behavior, matching semantics, performance limits, or any side effects. This is a minimal disclosure for a tool that queries an external SAP system.

    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, front-loaded sentence with no filler or repetition. It efficiently communicates the core purpose without wasting tokens.

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

    Completeness2/5

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

    For a tool with nine optional parameters, no output schema, no annotations, and a sibling tool, the description is too sparse. It omits key operational context such as how pagination works, what the response looks like, whether filters are combined, and when to prefer get_object_types.

    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%, so the schema fully documents all nine parameters. The tool description itself adds no parameter-level meaning beyond the schema, 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.

    Purpose4/5

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

    The description states a clear action (Query) and a specific resource (ABAP programs, classes, function modules, and other objects from SAP system). It distinguishes the tool from get_object_types in intent, but it does not explicitly differentiate it or name the sibling, so it stops just short of a 5.

    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 about when to use this tool versus get_object_types, when to use filters, or how to handle pagination. The extent of guidance is the sentence itself, which merely restates what the tool does.

    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, the description must carry behavioral disclosure. 'Get list' clearly implies a read-only operation, but it does not specify output format, ordering, pagination, or whether any authorization is needed. It is adequate for a simple list operation but not richly 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?

    A single concise sentence with no filler. The action and result ('list ... with descriptions') are front-loaded and every word earns its place.

    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?

    For a parameterless list tool, the description conveys the core behavior, but there is no output schema to document return structure and no mention of how the object types connect to the sibling query_abap_objects. Slightly more context would make it fully self-contained.

    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 no parameters and the schema confirms this with 100% coverage, so there is nothing for the description to add about parameter meaning. The no-parameter case naturally earns the baseline of 4.

    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 states a specific action ('Get list') and resource ('available object types'), and notes the output includes descriptions. It does not explicitly contrast with the sibling query_abap_objects, but the resource naming is distinct enough that the purpose is reasonably clear.

    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 about when to call this tool versus query_abap_objects, nor any context such as how the returned object types relate to querying ABAP objects. The agent must infer the tool's place in a workflow.

    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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