mcp-abap-keyword

by yynhr

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Latest release: v0.1.0
Disambiguation3/5
Some overlap exists between search_abap_keyword and get_abap_index, as both are described as methods for finding ABAP keywords. The descriptions clarify that one is a search and the other returns the full index, but the stated use cases overlap. Other tools like lookup_glossary and get_abap_topic are distinct.
Naming Consistency4/5
Tool names follow a consistent verb_noun pattern with snake_case, e.g., search_abap_keyword, get_abap_topic. Minor inconsistency is lookup_glossary not including 'abap' as a descriptor, but the pattern remains readable. Overall, the naming is predictable.
Tool Count5/5
With 6 tools, the server is well-scoped for its purpose of providing ABAP keyword documentation. Each tool serves a function in searching and browsing the documentation, and the count is within the ideal range.
Completeness4/5
The tool set covers searching keywords, browsing main topics, retrieving topic details, glossary lookup, and full index/subject directories. A minor gap is the lack of a direct tool for retrieving full documentation for a specific keyword beyond the index links, but the core browsing and search capabilities are well covered.
Average 3.7/5 across 6 of 6 tools scored. Lowest: 3.1/5.
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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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 alone must disclose behavioral traits. It states that it gets information but does not clarify return format, validation of the topic parameter, error handling, or any other side effects. This is minimal disclosure beyond the obvious read operation.
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 sentence, front-loaded with the verb and resource, and uses parenthetical examples compactly. There is no filler or redundant information.
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 one parameter and no output schema, so the description should convey what the agent will receive. It says 'detailed information' but not whether the output is text, structured data, or a list. For a simple tool, this is a noticeable but not severe 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 schema already documents the 'topic' parameter with examples, achieving 100% coverage. The description repeats similar examples in prose without adding new details like allowed values, case sensitivity, or default behavior. With high schema coverage, the baseline of 3 is appropriate.
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 verb 'Get' and the resource 'detailed information about a specific ABAP topic area', with concrete examples (Dictionary, CDS, RAP). This distinguishes it from sibling tools like search_abap_keyword and browse_main_topics, though it does not explicitly name alternatives.
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?
The description provides no guidance on when to use this tool versus alternatives. It implies use for a specific topic but does not mention when to choose search_abap_keyword or browse_main_topics instead, leaving the decision entirely to the agent.
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 are provided, so the description carries the behavioral disclosure burden. It does mention that the tool 'returns a categorized overview', which adds some clarity about the output, but it does not describe limitations, pagination, language specifics, or what 'main topics' includes beyond the title.
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 short, purposeful sentences. The first states the action and scope, and the second clarifies the expected result. There is no redundant or filler content.
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 zero-parameter browse tool with no output schema, the description provides enough context to understand the tool's core purpose and what it returns. The phrase 'categorized overview of available documentation sections' is concise yet sufficient, though slightly more detail about the category structure could improve completeness.
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 there is nothing additional to explain about parameter usage or semantics. The baseline of 4 applies because no parameter information is needed.
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 uses a specific verb ('Browse') with a clear resource ('all main topics in the ABAP Keyword Documentation') and adds a return summary ('categorized overview'). It is clear enough to distinguish from search/lookup siblings, though it does not explicitly differentiate from the similarly scoped 'get_abap_subjects'.
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?
The description provides no guidance on when to use this tool versus alternatives. It implies use for a high-level overview but does not state exclusions, prerequisites, or when to prefer a sibling tool like 'get_abap_subjects' or 'search_abap_keyword'.
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 are provided, so the description is the only source. It implies a read-only lookup operation and indicates that the output includes a definition and explanation, but it does not explicitly state side-effect-free behavior, error handling, or access requirements. For a simple lookup, this is minimally adequate.
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 clear sentence that efficiently conveys purpose without unnecessary words.
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?
The description sufficiently explains what the tool does for a simple single-parameter lookup. It does not include details on return format or edge cases, but the statement that it returns a definition and explanation is adequate given no output schema and low complexity.
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 already fully describes the 'term' parameter with examples. The description does not add additional semantic detail beyond restating that a term is looked up, so it does not elevate above the schema baseline.
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 tool's function: looking up a term in the ABAP Glossary to retrieve its definition and explanation. The verb 'look up' and specific resource 'ABAP Glossary' differentiate it from sibling tools like search_abap_keyword or browse_main_topics.
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?
There is no guidance on when to use this tool versus the sibling tools. It does not mention alternatives, prerequisites, or specific scenarios, such as when a user needs a formal glossary definition rather than a broader keyword search.
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 are provided, so the description carries the burden. It discloses that the tool returns matching keywords with documentation links, which is useful. However, it does not mention details such as case sensitivity, result limits, or whether any authentication is needed, leaving gaps for a search operation.
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 exactly two sentences, with the purpose stated first and the return value succinctly added. Every word earns its place, with no redundancy or filler.
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 (one parameter, no output schema), the description adequately clarifies what the tool does and what it returns. It could be slightly richer with mention of expected result format or edge cases, but for a search-style tool it is largely 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?
The schema covers the single parameter 'keyword' with a clear description and examples (100% coverage). The tool description adds no extra meaning beyond 'Search for ABAP keywords,' which is already implied by the schema. Baseline 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 uses the specific verb 'Search' and identifies the resource as 'ABAP keywords in the official ABAP Index,' which clearly distinguishes it from siblings like get_abap_index (which likely lists the index) and lookup_glossary (which suggests glossary terms). The return value is also stated, adding clarity.
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 searching ABAP keywords, but it does not explicitly state when to use this tool over sibling tools like lookup_glossary or get_abap_index. There are no direct exclusion criteria or alternative recommendations.
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 that the tool returns all entries and organizes them alphabetically, which adds context, but it does not mention potential response size, pagination, or explicitly confirm that this is a read-only operation. The description is honest but not richly detailed.
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 result. The second sentence adds a practical usage hint without unnecessary elaboration. Every phrase earns its place.
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 no-parameter getter, the description adequately covers what the tool does and what it returns. The main gap is the lack of explicit differentiation from the sibling search tool, which could mislead an agent in tool selection, but the description is otherwise complete for its simplicity.
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 input schema has zero parameters, so there is no parameter meaning to convey. The description appropriately focuses on the return value instead. Given the 0-parameter baseline of 4, this is a solid score.
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 complete ABAP Keyword Index with all entries' and specifies the return content: 'all keywords/terms with their documentation page references, organized alphabetically.' This specific verb+resource combination distinguishes it from sibling search_abap_keyword, which likely performs a targeted search.
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 provides an implied use case: 'Use this to let the LLM search for specific ABAP keywords,' but it does not explicitly contrast this with the alternative search_abap_keyword tool or state when to prefer one over the other. It lacks clear exclusions or alternative guidance.
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?
With no annotations, the description carries the full burden. It discloses that the tool returns all entries (no filtering), includes page references, and is alphabetically organized, implying a read-only directory operation. This is meaningful behavioral context beyond just 'get subjects.'
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 tight sentences: the first states what the tool does, the second states when to use it. No redundancy or irrelevant details, making it highly 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?
Given there is no output schema, the description appropriately summarizes the return content (subjects/topics with page references) and organization (alphabetical). It doesn't detail exact data structures, but for a zero-parameter directory tool, this is reasonably complete.
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 the schema is trivially complete. The baseline for 0 parameters is 4, and the description adds no parameter-specific details because 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?
The description clearly states the tool gets the complete ABAP Subject Directory, and specifies it returns all subjects/topics with documentation page references, organized alphabetically. It is well-scoped and distinguishes from siblings like search_abap_keyword by emphasizing 'complete' and 'all entries.'
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 explicitly says 'Use this to let the LLM search for specific ABAP subjects,' providing a clear use case. However, it does not mention alternatives or exclusions, so it lacks the 'when-not-to-use' guidance that would earn a 5.
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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