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jeremyclee

Dexcom Share MCP Server

by jeremyclee
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Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one returns a set of recent readings over a time window, while the other returns only the single most recent reading. There is no ambiguity about which to use for a given scenario.

    Naming Consistency5/5

    Both tool names use a consistent 'get_adjective_noun' pattern (get_glucose_readings and get_latest_reading), making the naming predictable and easy to understand.

    Tool Count3/5

    With only two tools, the surface feels thin for a glucose monitoring server, but it covers the essential use cases of retrieving current and recent data. The count is reasonable for a focused utility, though it leaves little room for additional functionality.

    Completeness3/5

    The server covers the primary use case of retrieving real-time glucose data. However, it lacks tools for historical retrieval (beyond 24 hours), setting alerts, managing device status, or user authentication, which are common interactions for a Dexcom integration.

  • Average 4.4/5 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

  • 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 clearly states the tool uses an 'unofficial Share API' and only provides 'real-time monitoring data', which is valuable context about limitations. However, it does not mention potential errors or rate limits, but the critical constraint is well covered.

    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 front-loaded with the purpose, followed by the key constraint and limitation. Every sentence adds value without waste.

    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 (2 parameters, no output schema, no nested objects), the description is sufficient to guide correct usage and set expectations. It could mention return format but that is not critical for a simple data retrieval. The limitation is well articulated.

    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 already provides descriptions for both parameters with ISO format examples and the 24-hour constraint. The description reinforces this but adds minimal new meaning beyond that. With 100% schema coverage, a baseline 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 states the tool retrieves 'recent glucose values within the last 24 hours', which is a specific verb+resource+time scope. It clearly distinguishes from the sibling 'get_latest_reading' by emphasizing the time range and use of the Share API.

    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?

    The description explicitly warns that both startDate and endDate must be within the last 24 hours, and that the tool cannot retrieve historical data beyond that window. This provides clear when-to-use guidance and implicitly differentiates from the sibling for the latest reading.

    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 must disclose behavioral traits. It explains the typical recency (5-15 minutes) and speed (fastest way), setting clear expectations for staleness and performance. It does not mention any destructive side effects or authentication needs, but given it is a zero-parameter, read-only tool, this is 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 extremely short at two sentences, each serving a distinct purpose: stating the core function and adding a usage tip. No words are wasted, and the key information is front-loaded in the first sentence. This is ideal for efficient agent parsing.

    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 has zero parameters, no output schema, and no annotations, the description is sufficiently complete for its complexity. It tells the user what to expect (most recent reading, speed) and implies the output is a single value. The only minor gap is not describing the return format (e.g., whether it includes timestamp or units), but for a tool with no output schema, the description cannot be expected to cover that.

    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 no parameters and schema description coverage is 100%, so there are no parameters to describe. The baseline expectation is 4, and the description adds no unnecessary parameter explanations. It correctly focuses on the tool's behavior rather than elaborating on a non-existent 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 uses a specific verb ('Get') and a specific resource ('most recent glucose reading'), and further clarifies it is the 'fastest way to check current glucose levels'. It clearly distinguishes the tool from its sibling 'get_glucose_readings' by implying it returns a single, latest reading rather than a list.

    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 states this is the 'fastest way to check current glucose levels', which implies it should be used when a quick, current snapshot is needed. It does not explicitly say when not to use it, but the distinction from the sibling tool (which likely returns multiple readings) is clear enough to guide selection.

    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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