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maboukerfa

AirTrail MCP Server

by maboukerfa
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Server Quality Checklist

50%
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  • Latest release: v0.1.0

  • Disambiguation4/5

    The three tools have distinct purposes (add, retrieve specific, list all), but add_flight lacks a description which slightly increases ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern, making them predictable.

    Tool Count4/5

    Three tools is slightly sparse but appropriate for a basic flight tracking server covering add, get, and list operations.

    Completeness3/5

    The set covers adding, retrieving, and listing flights, but lacks update and delete operations, which are notable gaps for a complete lifecycle.

  • Average 2.3/5 across 3 of 3 tools scored. Lowest: 1/5.

    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

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

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

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  • 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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  • Add related servers to improve discoverability.

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.

Tool Scores

  • Behavior1/5

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

    Tool has no description.

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

    Conciseness1/5

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

    Tool has no description.

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

    Completeness1/5

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

    Tool has no description.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Tool has no description.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose1/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Tool has no description.

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

    Usage Guidelines1/5

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

    Tool has no description.

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

  • Behavior2/5

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

    No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only mentions that the tool returns ICAO codes, but it does not state whether the operation is read-only, idempotent, or what happens on invalid flight numbers (e.g., error handling, null results). This is insufficient for safe usage.

    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?

    The description is two sentences, concise and front-loaded. The first sentence delivers the core purpose, and the second clarifies the return format (ICAO codes). No superfluous words, though the second sentence partially repeats the first.

    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?

    Given no output schema, the description partially explains return values (ICAO airport codes) but fails to specify if other itinerary details are included, how errors are conveyed, or any pagination/limitation. For a simple retrieval with one parameter, it is minimally adequate but lacking completeness.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the description must add meaning to the single parameter 'flight_number'. It merely says 'for a specific flight number' without specifying format, constraints, or examples. This adds little value over the schema.

    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 states the tool retrieves flight itinerary information for a specific flight number, including departure and arrival ICAO airport codes. The verb 'Retrieve' and resource 'flight itinerary information' are specific, and the scope is well-defined. However, it does not explicitly differentiate from sibling tools 'add_flight' and 'list_flights', so it lacks full comparative clarity.

    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?

    The description provides no guidance on when to use this tool versus alternatives like 'add_flight' or 'list_flights'. There is no mention of prerequisites, context, or exclusions, leaving the agent without decision-making support.

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

  • Behavior2/5

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

    With no annotations provided, the description must convey behavioral traits. It implies a read-only operation but does not explicitly state that it is nondestructive or safe. No mention of performance, limits, or side effects is 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?

    The description is a single concise sentence that conveys the core purpose without unnecessary words. It could be slightly expanded to include usage context but remains efficient.

    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 description lacks completeness for a list tool. It does not mention output format, pagination, ordering, or any constraints. Given no output schema, the agent learns nothing about the return structure, which is critical for invoking the tool correctly.

    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 tool has no parameters, and the schema coverage is 100% (trivially). Per baseline rule, 0 parameters earns a 4. The description does not need to add meaning beyond what the schema already provides.

    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 states the tool lists all flights from Airtrail, using a specific verb and resource. However, it does not differentiate from siblings beyond the name; the sibling tools add_flight and get_flight_itinerary suggest different purposes but are not explicitly contrasted.

    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 is provided on when to use this tool versus alternatives. The description does not mention that this tool is for obtaining a broad list, while get_flight_itinerary is for details on a specific flight, or add_flight for creating new entries.

    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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