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atorresg

location-mcp

by atorresg

Server Quality Checklist

67%
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  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool has a distinct purpose: IP geolocation, host IP detection, and reverse geocoding. No ambiguity or overlap.

    Naming Consistency5/5

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

    Tool Count5/5

    Three tools cover essential location operations without being excessive or insufficient for a focused location server.

    Completeness3/5

    Core operations are present, but forward geocoding (address to coordinates) is missing, which is a notable gap for a location service.

  • Average 3.8/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • Last stable release on
    • 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?

    With no annotations provided, the description must fully disclose behavioral traits. It mentions auto-detection and the data fields but omits critical details such as whether the operation is read-only, any error handling for invalid IPs, rate limits, or external service dependencies. This lack of depth reduces 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 two sentences long, directly stating the tool's purpose and a key behavioral note about auto-detection. Every sentence adds value with no unnecessary wording.

    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 simplicity (2 parameters, no output schema, no nested objects), the description covers the essential functionality and auto-detection. However, it lacks details about data sources, accuracy, or privacy implications, leaving the agent with unanswered questions for a geolocation service.

    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 describes both parameters (ip and format) with 100% coverage, including the auto-detection behavior for ip. The description reinforces this but adds minimal new semantic value beyond what the schema provides, meriting the baseline score.

    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 that the tool looks up geolocation data for an IP address and lists the types of data returned. It also mentions auto-detection if no IP is provided. However, it does not differentiate from sibling tools (get_my_ip, reverse_geocode), missing an opportunity to clarify scope.

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

    Usage Guidelines3/5

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

    The description implies usage for geolocation lookups and explicitly notes that omitting the IP triggers auto-detection. It provides no when-not-to-use guidance or explicit comparison to siblings, leaving the agent to infer context.

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

  • Behavior3/5

    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 indicates the output is a human-readable address with administrative details, adding value beyond the schema. However, it does not mention error handling, result accuracy, rate limits, or authentication requirements. The description is transparent about inputs and output essence but leaves gaps.

    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, clear sentence that is front-loaded with the action. It avoids unnecessary words and covers the main purpose. It could be slightly more concise, but it is efficient and includes useful detail (list of admin details). No 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 no output schema, the description explains the return value (address with admin details). It does not detail exact fields for json vs text, but the format parameter description in the schema partially covers that. For a low-complexity tool, the description is fairly complete, though it could mention error responses or limitations.

    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 coverage is 100%, with each parameter documented clearly (latitude range, longitude range, format enum). The description does not add additional meaning to the parameters beyond what the schema already provides. Baseline for high coverage is 3, and the description does not exceed that.

    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 clearly states the tool's purpose: reverse geocoding a latitude/longitude pair into a human-readable address with administrative details. The verb 'reverse geocode' is specific and directly conveys the core function. It distinguishes itself from sibling tools (geolocate_ip, get_my_ip) which deal with IP-based location, not coordinates.

    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 implies appropriate usage: given coordinates, get an address. It doesn't explicitly state when to use this versus alternatives, but the tool name and description make the context clear. Sibling tools are for IP geolocation, so the differentiation is implicit. No exclusions are provided, but the guidance is sufficient for an AI agent to infer correct usage.

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

  • Behavior3/5

    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 describes the operation but does not disclose any behavioral traits such as network dependencies, potential latency, or error conditions. While it is not misleading, it lacks additional context beyond the basic functionality.

    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 concise at two sentences, front-loading the core purpose. Every sentence is informative and there is no extraneous text.

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

    Completeness5/5

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

    Given the low complexity of the tool and the complete schema documentation for the parameter, the description provides adequate context. No output schema is present, but the return value is implicitly the IP address, which is sufficient.

    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% as the single parameter 'format' is fully described in the schema. The description adds no additional 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.

    Purpose5/5

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

    The description clearly states the tool detects and returns the public IP address of the host. It uses a specific verb ('Detect and return') and resource ('public IP address'), and is well-distinguished from sibling tools like geolocate_ip and reverse_geocode.

    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 explicitly mentions when the tool is useful ('when the LLM needs to know the public-facing IP'), providing clear context. However, it does not provide explicit exclusions or mention when not to use it.

    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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