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yunkee-lee

MCP Naver Maps

by yunkee-lee
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

    The two tools have clearly distinct purposes: geocode handles address-to-coordinate conversion, while localSearch finds registered places. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.

    Naming Consistency5/5

    Both tools follow a consistent naming pattern using camelCase (geocode, localSearch) with descriptive verb-noun structures. The naming is uniform and predictable across the set.

    Tool Count2/5

    With only two tools, the server feels under-scoped for a maps domain. While geocoding and local search are core functions, typical maps services include additional operations like routing, place details, or reverse geocoding, making this set appear incomplete.

    Completeness2/5

    For a maps server, there are significant gaps in coverage. Missing tools for routing, reverse geocoding, place details, or map visualization limit an agent's ability to handle common mapping workflows, leading to potential dead ends in tasks.

  • Average 3/5 across 2 of 2 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.

  • 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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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 carries full burden for behavioral disclosure. It states what the tool does but doesn't mention rate limits, authentication requirements, error conditions, response format, or whether this is a read-only operation. For a search tool with external API dependencies, this is insufficient behavioral context.

    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 purpose without unnecessary words. It's appropriately sized for a search tool and gets straight to the point with zero wasted text.

    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?

    For a search tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the response contains (e.g., place details, addresses, ratings), doesn't mention API limitations or authentication, and provides no guidance relative to the sibling tool. The agent would need to guess about important operational aspects.

    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 description adds no parameter information beyond what's already in the schema, which has 100% coverage. The schema fully documents all three parameters with descriptions, constraints, and defaults. The baseline score of 3 reflects adequate schema coverage without additional value from the description.

    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 action ('Searches for') and resource ('places registered with Naver's local service'), providing a specific purpose. However, it doesn't differentiate from the sibling tool 'geocode' which likely handles location-based searches, leaving room for ambiguity about when to use each.

    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. With a sibling tool 'geocode' available, there's no indication of whether this tool is for general place searches versus coordinate-based lookups, leaving the agent to guess about appropriate contexts.

    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 carries the full burden of behavioral disclosure. While 'searches' implies a read-only operation, it doesn't specify details like rate limits, authentication needs, error handling, or what 'address information' includes (e.g., coordinates, formatted address). This is a significant gap for a tool with no annotation coverage.

    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 directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy to parse quickly. Every word earns its place.

    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 moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output format. Without an output schema, the description should ideally hint at what 'address information' includes, but it doesn't, leaving gaps in completeness.

    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 has 100% description coverage, with clear documentation for both parameters (address and language). The description adds no additional meaning beyond the schema, such as examples or usage notes. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.

    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: 'Searches for address information related to the entered address.' This specifies the verb ('searches for') and resource ('address information'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from the sibling tool 'localSearch', which might have overlapping functionality.

    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. It doesn't mention the sibling tool 'localSearch' or any other context for usage, such as prerequisites or exclusions. This leaves the agent with no explicit direction on tool selection.

    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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