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Francis235

AMap MCP Server

by Francis235
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
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 has a clear, distinct purpose focused on weather queries.

    Naming Consistency5/5

    The single tool name follows a clear verb_noun pattern (query_weather), and with only one tool, there is no inconsistency to evaluate. The naming is straightforward and descriptive.

    Tool Count2/5

    One tool is too few for a server named 'AMap MCP Server', which suggests a broader mapping or location service domain. A single weather query tool feels thin and incomplete for this apparent scope.

    Completeness1/5

    The server is severely incomplete for a mapping service domain. There are obvious gaps such as geocoding, routing, place search, or map display tools. The single weather tool does not provide meaningful coverage of the expected functionality.

  • Average 3.2/5 across 1 of 1 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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the service provider ('Amap') but fails to describe key traits such as rate limits, authentication needs, error handling, or what the response format looks like. For a query tool with zero annotation coverage, this is a significant gap in transparency.

    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 appropriately sized and front-loaded, with the core purpose stated first followed by parameter details. Both sentences earn their place by providing essential information without redundancy. The structure is clear and efficient for a simple tool.

    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 the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate but lacks completeness. It covers the basic purpose and parameter but omits details on response format, error cases, and service constraints. For a query tool, this leaves gaps in understanding how to interpret results.

    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 description adds meaningful context for the single parameter 'city' by specifying it as 'The city to query the weather,' which clarifies its role beyond the schema's basic title. With 0% schema description coverage and only one parameter, this adequately compensates, though it could detail format expectations (e.g., city names, language).

    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's purpose as 'Query the weather of a given city,' specifying the verb 'query' and resource 'weather' with the target 'city.' It distinguishes the service provider as 'Amap,' but since there are no sibling tools, full differentiation isn't needed. However, it could be more specific about what weather data is returned.

    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 limitations. It only states the basic function without context about availability, accuracy, or when it might fail. With no sibling tools, explicit alternatives aren't required, but general usage context is missing.

    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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  • Evaluate tool definition quality.

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