Amap (Gaode Maps) MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have completely distinct purposes: one retrieves location data from an IP address, while the other searches for points of interest near given coordinates. There is no overlap in functionality or ambiguity in their intended use.
Naming Consistency5/5Both tools follow a consistent verb_noun naming pattern (locate_ip and search_nearby), using clear, descriptive verbs that align with their actions. The naming style is uniform and predictable across the set.
Tool Count2/5With only two tools, the server feels under-scoped for a mapping service like Amap, which typically involves broader functionality such as routing, geocoding, or traffic data. This limited set may hinder agents from performing comprehensive mapping-related tasks.
Completeness2/5The toolset is severely incomplete for a maps domain, lacking essential operations like geocoding addresses, calculating routes, or retrieving traffic information. Agents will face significant gaps when trying to handle common mapping workflows.
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
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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 output format but doesn't describe error handling, rate limits, authentication needs, or whether the tool is read-only or has side effects. For a tool with no 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose and output. It avoids unnecessary words, though it could be slightly more structured (e.g., separating purpose from output details).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema, the description is minimally adequate. However, it lacks behavioral context (e.g., error cases, performance), which is needed since no annotations are provided. The output schema likely covers return values, so the description doesn't need to detail them.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the parameter 'ip' documented as '用户的ip地址' (user's IP address). The description doesn't add meaning beyond the schema, such as explaining default behavior when 'ip' is null or providing examples. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '获取用户的 IP 地址定位信息' (get user's IP address location information) and specifies the output '返回省市区经纬度等信息' (returns province, city, district, latitude/longitude, etc.). It uses specific verbs and resources, though it doesn't explicitly differentiate from the sibling tool 'search_nearby'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'search_nearby'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the purpose alone.
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 carries the full burden of behavioral disclosure. It mentions the basic operation (search and return POI list) but doesn't describe important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or what happens when no results are found. For a search tool with 6 parameters and no annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for the tool's complexity and front-loads the essential information (search based on location/keywords, returns POIs within radius). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which should document return values), no annotations, and 100% schema coverage for parameters, the description provides adequate basic context. However, for a search tool with pagination parameters and no behavioral annotations, the description could better address usage patterns, result limitations, or common scenarios. It's minimally viable but lacks depth for optimal agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 6 parameters thoroughly. The description mentions '经纬度和关键词' (longitude/latitude and keywords) and '指定半径' (specified radius), which aligns with parameters in the schema but doesn't add meaningful semantic context beyond what's already in the parameter descriptions. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '根据经纬度和关键词进行周边搜索,返回指定半径内的 POI 列表' (Search nearby based on longitude/latitude and keywords, returning a list of POIs within a specified radius). It specifies the verb ('搜索' - search), resource ('POI 列表' - POI list), and scope ('周边' - nearby/within radius). However, it doesn't explicitly differentiate from the sibling tool 'locate_ip', which appears to be a different type of location tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'locate_ip' or any other potential alternatives. There's no information about prerequisites, appropriate contexts, or when this tool would be preferred over other search or location tools.
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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