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michaelahern

Airthings Consumer MCP Server

by michaelahern

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.
  • This repository includes a README.md file.

  • This repository includes a LICENSE file.

  • Latest release: v1.1.0

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • This server provides 1 tool. View schema
  • No known security issues or vulnerabilities reported.

    Report a security issue

  • Are you the author?

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Tool Scores

  • Behavior2/5

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

    No annotations are provided, so the description must carry full behavioral disclosure. It mentions 'current' sensor readings implying real-time data, but lacks critical details: whether it returns all devices or requires selection, caching behavior, rate limits, offline device handling, or what specific sensor types (CO2, radon, etc.) are included.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence with no redundant words. Information density is high. The sentence structure front-loads the action ('Get information') and immediately qualifies the scope, making it easy to parse.

    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?

    Without an output schema or annotations, the description should compensate by describing the return structure or data freshness guarantees. It mentions both devices and readings but doesn't clarify if this returns a list, single device, or structured sensor data, leaving ambiguity about the response format.

    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?

    Baseline 4 applies as there are zero parameters. The description appropriately requires no parameter explanation since the schema is empty. No penalty for lack of parameter detail when none exist.

    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 clearly identifies the resource (Airthings air quality monitoring devices) and what is retrieved (device information and current sensor readings). The verb 'Get' is slightly generic but the scope is specific and unambiguous.

    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 explicit guidance on when to invoke this tool versus alternatives. While the domain (air quality monitoring) implies usage context, there are no mentions of prerequisites, triggers like 'when user asks about indoor air quality', or conditions where this should be preferred over other environment tools.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

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{
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  ]
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How to make a release?

A "release" on Glama is not the same as a GitHub release. To create a Glama release:

  1. Claim the server if you haven't already.
  2. Go to the Dockerfile admin page, configure the build spec, and click Deploy.
  3. Once the build test succeeds, click Make Release, enter a version, and publish.

This process allows Glama to run security checks on your server and enables users to deploy it.

How to add a LICENSE?

Please follow the instructions in the GitHub documentation.

Once GitHub recognizes the license, the system will automatically detect it within a few hours.

If the license does not appear on the server after some time, you can manually trigger a new scan using the MCP server admin interface.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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.

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