mcp-meituan-ip
Servidor MCP mcp-meituan-ip
Componentes
Recursos
El servidor implementa un sistema de almacenamiento de notas simple con:
Nota personalizada: esquema URI para acceder a notas individuales
Cada recurso de nota tiene un nombre, una descripción y un tipo MIME de texto simple.
Indicaciones
El servidor proporciona un único mensaje:
resumir-notas: Crea resúmenes de todas las notas almacenadas
Argumento opcional "estilo" para controlar el nivel de detalle (breve/detallado)
Genera un mensaje que combina todas las notas actuales con la preferencia de estilo.
Herramientas
El servidor implementa una herramienta:
add-note: Agrega una nueva nota al servidor
Toma "nombre" y "contenido" como argumentos de cadena requeridos
Actualiza el estado del servidor y notifica a los clientes sobre los cambios de recursos.
Related MCP server: browser-use MCP server
Configuración
[TODO: Agregar detalles de configuración específicos para su implementación]
Inicio rápido
Instalar
Escritorio de Claude
En MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json En Windows: %APPDATA%/Claude/claude_desktop_config.json
Desarrollo
Construcción y publicación
Para preparar el paquete para su distribución:
Sincronizar dependencias y actualizar el archivo de bloqueo:
uv syncDistribuciones de paquetes de compilación:
uv buildEsto creará distribuciones de origen y de rueda en el directorio dist/ .
Publicar en PyPI:
uv publishNota: Deberás configurar las credenciales de PyPI a través de variables de entorno o indicadores de comando:
Token:
--tokenoUV_PUBLISH_TOKENO nombre de usuario/contraseña:
--username/UV_PUBLISH_USERNAMEy--password/UV_PUBLISH_PASSWORD
Depuración
Dado que los servidores MCP se ejecutan en stdio, la depuración puede ser complicada. Para una experiencia óptima, recomendamos usar el Inspector MCP .
Puede iniciar el Inspector MCP a través de npm con este comando:
npx @modelcontextprotocol/inspector uv --directory D:\idea-work\mcp-meituan-ip run mcp-meituan-ipAl iniciarse, el Inspector mostrará una URL a la que podrá acceder en su navegador para comenzar a depurar.
Available Tools
2 toolsget-ip-locC
获取指定ip的大致位置与经纬度信息
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes |
TDQS
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.
Is 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.
Given 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.
Does 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.
Does 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.
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 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.
get-latlngC
根据经纬度获取详细位置信息
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | ||
| lng | Yes |
TDQS
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.
Is 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.
Given 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.
Does 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.
Does 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.
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 '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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v1.0.0- First observed
get-ip-loc - First observed
get-latlng
TDQS
Scored across 2 tools
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.
Both 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.
With 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.
The 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.
Maintenance
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