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CoreBaseHQ

coremcp

by CoreBaseHQ
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Server Quality Checklist

75%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely different purposes—one retrieves daily sales data, the other lists database procedures—so there is no ambiguity or overlap between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (get_daily_sales, list_procedures), making the naming predictable and easy to understand.

    Tool Count2/5

    With only two tools, the server feels too sparse for the broad-sounding name 'coremcp'. The tools cover unrelated domains, suggesting the surface is underdeveloped.

    Completeness1/5

    The tool set is severely incomplete: there is no way to execute procedures (despite list_procedures suggesting it), no CRUD operations on sales data, and no clear domain cohesion. Agents will find the surface insufficient for practical use.

  • Average 3.3/5 across 2 of 2 tools scored.

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

    • 1 of 2 community issues answered or closed in the last 6 months
    • 2 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under Apache 2.0.

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

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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

  • Behavior1/5

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

    The description claims a read-only retrieval operation, but annotations indicate destructiveHint=true, implying potential modification. This is a clear contradiction. No further behavioral details are provided to resolve this inconsistency.

    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?

    Single sentence, front-loaded with the core action, no redundant information. Perfectly concise for a simple tool.

    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?

    The tool is simple, but the description fails to explain what the 'daily sales summary' includes, the return format, or error handling. The annotation contradiction is a major gap that remains unaddressed.

    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% (one parameter 'date' described as 'date (date)'). The description adds context about 'daily sales summary' but does not add new meaning beyond 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 clearly states it retrieves a daily sales summary for a specific date, with a clear verb ('retrieves') and resource ('daily sales summary'). It distinguishes from sibling tools like get_pending_orders or get_top_customers.

    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 on when to use this tool versus alternatives, no exclusion criteria, and no context about prerequisites or best use cases. The description simply states what it does without usage direction.

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

  • Behavior1/5

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

    Annotations indicate destructiveHint=true and readOnlyHint=false, contradicting the description's 'Lists' which implies a read-only operation. The description does not address this paradox or explain any potential side effects, leading to agent confusion.

    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 long, front-loads the core purpose, and includes a sibling reference. No unnecessary information, 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 simple tool with one parameter and no output schema, the description covers listing procedures with parameters. However, the contradiction between annotations and description is unresolved, and no output format hint is given, making it incomplete for safe usage.

    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 single parameter 'source_name' is fully described in the schema (100% coverage). The description adds no further semantic value beyond what the schema provides, so a baseline score of 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 clearly states it lists stored procedures with their parameters in a database source. It differentiates from sibling 'execute_procedure' by directing users to that tool for execution.

    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 gives clear context for use (listing procedures) and recommends 'execute_procedure' as an alternative for running. It does not explicitly mention when to avoid this tool or compare with other list siblings, but the resource-specific naming provides sufficient guidance.

    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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  • 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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