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gemyago

HelloWorld MCP Server

by gemyago
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: 'add' performs a mathematical operation on numbers, while 'hello' handles a greeting interaction. There is no overlap or ambiguity between these functions, making tool selection straightforward for an agent.

    Naming Consistency5/5

    Both tool names are simple, lowercase verbs ('add' and 'hello') that clearly indicate their actions. While they don't follow a strict verb_noun pattern, the naming is perfectly consistent in style and readability for this minimal set.

    Tool Count2/5

    With only two tools, this server feels extremely thin and under-scoped for any meaningful domain. The tools are trivial and unrelated, suggesting either a demo/test server or one with significant missing functionality for practical use.

    Completeness1/5

    The server lacks a coherent domain, making completeness impossible to assess meaningfully. The tools are isolated operations (math and greeting) with no logical connection or coverage of any workflow, representing a severely incomplete surface for any real-world purpose.

  • Average 3.1/5 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

  • This repository is licensed under MIT License.

  • 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Add two numbers together' implies a simple computation but doesn't disclose any behavioral traits like error handling, precision limits, or return format. It's minimal and lacks context about what the tool actually does beyond the basic 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 extremely concise ('Add two numbers together')—a single sentence that front-loads the core purpose with zero waste. Every word earns its place, making it highly efficient and well-structured for its simplicity.

    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?

    Given the tool's low complexity (simple arithmetic), no annotations, no output schema, and high schema coverage, the description is minimally adequate. It states what the tool does but lacks details on behavior or output, making it complete enough for basic understanding but with clear gaps for an agent needing full context.

    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 has 100% description coverage with clear parameter descriptions ('First number', 'Second number'), so the baseline is 3. The description 'Add two numbers together' aligns with the schema but doesn't add meaningful semantic context beyond what's already documented in the structured fields.

    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 'Add two numbers together' clearly states the verb ('add') and resource ('two numbers'), making the purpose immediately understandable. However, it doesn't distinguish from sibling tools (only 'hello' exists, which is unrelated), so it doesn't fully meet the highest standard of sibling differentiation.

    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 doesn't mention any context, prerequisites, or exclusions. While the sibling tool 'hello' is unrelated, there's no explicit comparison or usage context provided.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden for behavioral disclosure. 'Say hello to someone' implies a read-only, non-destructive action, but it doesn't specify whether this requires authentication, has rate limits, returns structured data, or how the greeting is delivered (e.g., console output, API response). For a tool with zero annotation coverage, this leaves significant behavioral gaps.

    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, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple greeting tool. Every word earns its place without redundancy or unnecessary elaboration.

    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?

    Given the tool's low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, usage context, or output format. For such a simple tool, this might be sufficient, but it doesn't provide complete guidance for optimal agent use.

    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%, with the single parameter 'name' fully documented in the schema as 'The name of the person to greet' with a default value. The description doesn't add any parameter details beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without extra value.

    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 'Say hello to someone' clearly states the tool's purpose with a specific verb ('say hello') and target ('to someone'). It distinguishes from the sibling tool 'add' which likely performs a different function. However, it doesn't specify the exact output format or delivery mechanism, keeping it from a perfect score.

    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 doesn't mention any context, prerequisites, or comparisons with the sibling tool 'add'. The agent must infer usage solely from the tool name and description without explicit direction.

    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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