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Ricoledan

mcp-onprem-starter

by Ricoledan
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: list_records for querying/searching with pagination, and create_record for inserting new records. No overlap or ambiguity exists.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (list_records, create_record), making the API predictable and easy to navigate.

    Tool Count3/5

    At 2 tools, the set is on the thin side, but for a 'starter' server it could be intentionally minimal. However, the reference to get_record suggests at least one more expected tool.

    Completeness2/5

    The set is missing get_record, update_record, and delete_record. list_records explicitly instructs agents to use get_record, but that tool does not exist, creating a clear dead end and significant coverage gap.

  • Average 4.7/5 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 is passing

  • 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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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

  • Behavior5/5

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

    Discloses critical behaviors beyond annotations: dry-run default, the need for confirm=true, and the ALLOW_WRITES deployment flag. This adds substantial context that annotations (readOnlyHint false, destructiveHint true) do not fully cover.

    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?

    Two sentences, no fluff, front-loaded with purpose then key behavioral caveats. Every sentence 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?

    Covers the essential invocation behavior (dry-run, confirm, ALLOW_WRITES) and gives a hint about return ('preview of exact payload'). It lacks details on error responses or execute-mode return, but is sufficient for a simple create tool with no output schema.

    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?

    Schema covers 100% of parameters with descriptions, but the description adds the crucial ALLOW_WRITES dependency and reinforces confirm flag semantics, going slightly beyond the schema.

    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 'Create a new record in the upstream system', using a specific verb and resource. It distinguishes from the sibling 'list_records' by its create action and mentions the upstream system.

    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?

    Provides clear usage context: creation requires confirm=true to execute, defaults to dry-run, and requires ALLOW_WRITES enabled. However, it does not explicitly mention using the sibling tool for reading, so it's not a full 5.

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

  • Behavior5/5

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

    Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds significant behavioral context beyond annotations: the result is a 'bounded page' with a total-matched count and a truncated flag, explaining how to interpret and act on truncation, which is valuable for using the tool correctly.

    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 concise and well-structured: a single sentence stating purpose, followed by a sentence covering paging behavior and an alternative tool. Every word earns its place, with no redundant or filler content.

    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 complexity (pagination, filtering, total count, truncation) and the lack of an output schema, the description explains the return shape and expected behavior thoroughly. It also provides a pointer to get_record for full details, making the description functionally complete for an agent.

    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 coverage is 100% with descriptions for both limit and query, so the schema carries the parameter semantics. The description adds minimal extra parameter meaning—it mentions 'optionally filtered by a search query' and 'bounded page' which aligns with existing schema fields but doesn't provide new details beyond what's already documented.

    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: 'List records from the upstream system, optionally filtered by a search query.' It distinguishes from the sibling tool create_record by focusing on read-only listing, and also contrasts with get_record for fetching a single record.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Provides explicit guidance on when to use this tool vs. alternatives: 'Use get_record to fetch one record in full.' Also gives actionable advice on handling truncation ('call again with a narrower query if truncated is true') and clarifies the meaning of the truncated flag.

    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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