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mcp-server-starter-kit

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Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools are completely distinct: 'ping' provides a liveness check, while 'http_get_json' performs an HTTP request. No overlap or ambiguity exists between them.

    Naming Consistency2/5

    The tool names are both lowercase but follow different patterns: 'ping' is a single verb, while 'http_get_json' uses a verb_noun structure with a prefix. The lack of a consistent pattern makes the set feel ad hoc.

    Tool Count3/5

    With only two tools, the set is thin and borderline. For a starter kit, it is minimal but not entirely unreasonable, yet it still feels sparse for most practical purposes.

    Completeness3/5

    The server provides only a basic health check and a JSON GET utility. There are no other operations, and the domain is undefined, so it covers a minimal demo but lacks any meaningful workflow or lifecycle.

  • Average 4.3/5 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 status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    With no annotations, the description carries the full burden of behavioral disclosure. It mentions the https-only rule, SSRF host allowlist, and request timeout, giving the agent important constraints. It does not describe error handling or response format beyond JSON, but the core safety behavior is 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?

    The description is a single, front-loaded sentence that immediately states the tool's purpose and key constraints without extraneous words. Every clause adds value.

    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 two-parameter GET tool, the description covers the essential purpose, input constraints, and timeout, and it notes the return type (JSON body). It doesn't specify error handling or non-JSON responses, but given the lack of output schema and complexity, it is sufficiently 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 both parameters with descriptions (100% coverage), so the baseline is 3. The description adds some context about the URL being allowlisted and the timeout, but largely restates what the schema already provides.

    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 explicitly states the action 'GET an allowlisted https:// URL' and the result 'return the JSON body.' It clearly distinguishes from the only sibling 'ping' by focusing on fetching JSON content rather than connectivity checks.

    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 provides clear context for when the tool is applicable: it works only on allowlisted https URLs and enforces a timeout. However, it does not explicitly contrast with 'ping' or list exclusions, so it lacks explicit 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?

    No annotations are provided, so the description carries the full burden. It discloses the behavioral outcome ('Returns server name, version, and current time') and implies a read-only operation through 'Liveness check', which is transparent for a simple ping tool. It does not explicitly state lack of side effects, but that is inherent to the liveness check concept.

    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: two short sentences with no unnecessary words. It front-loads the core purpose ('Liveness check') and then provides the key return details. Every word earns its place.

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

    Completeness5/5

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

    Given the tool's simplicity (zero params, no output schema), the description covers what is needed: it names the action and describes the exact response content. There is no ambiguity about what the tool does or returns, making it complete for its context.

    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?

    There are zero parameters, so the description does not need to explain any. With no parameters, the baseline for this dimension is 4. The description appropriately focuses on the return value rather than params.

    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: 'Liveness check' and specifies exactly what it returns ('server name, version, and current time'). This distinguishes it from the sibling tool 'http_get_json', which is a generic HTTP GET, by indicating a specific health-check purpose with a defined response payload.

    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 phrase 'Liveness check' implies usage for verifying server health or connectivity, but there is no explicit when/when-not guidance or mention of alternatives like 'http_get_json'. The context is implied rather than stated, so it falls short of a clear usage directive.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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