mcp-meituan-ip
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have clearly distinct purposes: one maps IP addresses to locations, while the other maps latitude/longitude coordinates to detailed location information. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the input type.
Naming Consistency5/5Both tools follow a consistent verb_noun naming pattern with hyphens (get-ip-loc and get-latlng), using the same verb 'get' and descriptive nouns. This predictable structure enhances readability and usability.
Tool Count3/5With only two tools, the server feels thin for a location/geolocation service, as it lacks operations like reverse geocoding, batch processing, or error handling. While the tools are complementary, the scope is minimal and may limit agent workflows.
Completeness3/5The server covers basic IP and coordinate lookups but has notable gaps, such as missing reverse geocoding from location to coordinates, validation tools, or support for multiple IPs. This could lead to agent workarounds or failures in more complex scenarios.
Average 2.9/5 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.
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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 states the tool retrieves '详细位置信息' (detailed location information), implying a read-only operation, but doesn't specify what 'detailed' includes (e.g., address, city, country), whether there are rate limits, authentication needs, error handling, or data freshness. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.
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: '根据经纬度获取详细位置信息'. It's front-loaded with the core purpose, has zero redundant words, and appropriately sized for a simple tool. Every part of the sentence contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no output schema, no annotations), the description is incomplete. It lacks details on return values (what 'detailed location information' entails), error cases, usage boundaries compared to siblings, and parameter specifics. Without annotations or output schema, the description should provide more context to enable correct tool invocation and result interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 2 parameters (lat, lng) with 0% description coverage, meaning the schema provides no semantic context. The description mentions '经纬度' (latitude and longitude), which maps to the parameters, but adds minimal value beyond naming them. It doesn't explain format (e.g., decimal degrees, strings), units, range, or examples, failing to compensate for the low schema coverage.
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: '根据经纬度获取详细位置信息' (Get detailed location information based on latitude and longitude). It specifies the verb '获取' (get) and resource '详细位置信息' (detailed location information), making the action and target explicit. However, it doesn't differentiate from the sibling tool 'get-ip-loc', which appears to serve a similar purpose but uses IP instead of coordinates.
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 'get-ip-loc' or explain scenarios where latitude/longitude input is preferred over IP-based location lookup. There's no context about prerequisites, exclusions, or comparative use cases, leaving the agent to infer usage based on parameter differences 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does (get location info for an IP) but lacks details on behavioral traits such as rate limits, error handling, data sources, accuracy levels, or authentication needs. For a tool with no annotations, this leaves significant gaps in understanding how it operates.
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 in Chinese: '获取指定ip的大致位置与经纬度信息'. It is front-loaded with the core action and resource, with zero wasted words. Every part of the sentence directly contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a lookup tool with no annotations, 1 parameter, and no output schema), the description is incomplete. It explains the basic purpose but lacks crucial context such as return format, error cases, limitations (e.g., '大致' - approximate implies inaccuracy), or how results are structured. Without an output schema, the description should ideally cover return values, which it does not.
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 1 parameter ('ip') with 0% description coverage, meaning the schema provides no semantic details. The description adds value by specifying that the IP is '指定' (specified), implying it's a required input for lookup. However, it doesn't elaborate on format (e.g., IPv4 vs. IPv6), validation, or examples. With low schema coverage, the description compensates minimally but not fully.
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: '获取指定ip的大致位置与经纬度信息' (Get the approximate location and latitude/longitude information for a specified IP). It uses specific verbs ('获取' - get) and resources ('ip', '位置', '经纬度'), making the function unambiguous. However, it doesn't explicitly differentiate from the sibling tool 'get-latlng', 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 Guidelines2/5Does 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 the sibling 'get-latlng'. It doesn't mention any prerequisites, constraints, or scenarios where this tool is preferred or should be avoided. Usage is implied from the purpose but not explicitly stated.
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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