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henrikaslund

ALECS - MCP server for Akamai

by henrikaslund
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TypeScript
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Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'property.list' has a clearly distinct purpose of listing Akamai CDN properties, and no other tools exist to cause confusion.

    Naming Consistency5/5

    The naming pattern is perfectly consistent as there is only one tool. It follows a clear verb_noun structure ('property.list'), and with no other tools to compare against, there is no inconsistency in naming conventions.

    Tool Count2/5

    A single tool is too few for a server intended to interact with Akamai's CDN properties, which typically involve operations like create, update, delete, or get details. This minimal set severely limits functionality and suggests an incomplete implementation for the domain.

    Completeness1/5

    The tool set is severely incomplete for managing Akamai CDN properties. It only provides listing functionality, missing essential CRUD operations such as create, read (get details), update, and delete, as well as other domain-specific actions like activating or deactivating properties, which are critical for a comprehensive CDN management surface.

  • Average 2.9/5 across 1 of 1 tools scored.

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

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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

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden for behavioral disclosure. 'List' implies a read operation, but the description doesn't mention authentication requirements, rate limits, pagination behavior, error conditions, or what format the properties are returned in. For a tool with zero annotation coverage, this is insufficient.

    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 a single, efficient sentence that states the core functionality without any wasted words. It's appropriately sized for a simple list operation and gets straight to the point. Every word earns its place.

    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?

    Given no annotations, no output schema, and a read operation with three parameters, the description is incomplete. It doesn't explain what 'properties' are in this context, what data they contain, whether results are paginated, or what authentication is required. For a tool that likely returns structured data, more context is needed.

    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%, so the schema already documents all three parameters. The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain how parameters interact, which combinations are valid, or provide examples. Baseline 3 is appropriate when schema does the documentation work.

    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 verb ('List') and resource ('Akamai CDN properties'), making the tool's purpose immediately understandable. It doesn't distinguish from siblings since none exist, but it's specific enough to know this retrieves CDN property listings. A 5 would require sibling differentiation which isn't applicable here.

    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, prerequisites, or contextual constraints. It simply states what the tool does without indicating appropriate usage scenarios. With no siblings, the bar is lower, but still lacks any usage context.

    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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