Skip to main content
Glama
geolabel

geolabel-mcp

by geolabel

MCP-сервер GeoLabel

Превращайте GPS-координаты в контекст местоположения, готовый для ИИ — для Claude Desktop, Claude Code и любого MCP-совместимого помощника.

Что он делает

Отправляйте координаты. Получайте название места, категорию и часы работы в реальном времени:

{
  "label": "Walmart",
  "category": "supermarket",
  "is_open": true,
  "closes_at": "23:00",
  "opening_hours": "Mo-Su 06:00-23:00"
}

После этого Claude сможет ответить: «Вы находитесь в Walmart, который закрывается через 47 минут».


Related MCP server: Geo MCP Worker

Быстрая настройка

1. Получите API-ключ GeoLabel

Бесплатно на geolabel.dev — 100 запросов в день, кредитная карта не требуется.

2. Добавьте в своего агента

Выберите свой клиент ниже.


Claude Desktop

Отредактируйте ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "geolabel": {
      "command": "uvx",
      "args": ["geolabel-mcp"],
      "env": {
        "GEOLABEL_API_KEY": "glk_your_key_here"
      }
    }
  }
}

Перезапустите Claude Desktop. Инструмент GeoLabel появится в списке инструментов.

Claude Code

claude mcp add geolabel -- uvx geolabel-mcp
export GEOLABEL_API_KEY=glk_your_key_here

Hermes Agent

Отредактируйте ~/.hermes/config.json:

{
  "mcpServers": {
    "geolabel": {
      "command": "uvx",
      "args": ["geolabel-mcp"],
      "env": {
        "GEOLABEL_API_KEY": "glk_your_key_here"
      }
    }
  }
}

Подробнее см. в документации Hermes Agent MCP.

OpenClaw

# Register the server
openclaw mcp set geolabel \
  --command uvx \
  --args geolabel-mcp \
  --env GEOLABEL_API_KEY=glk_your_key_here

# Verify it's registered
openclaw mcp list

Подробнее см. в документации OpenClaw MCP.


3. Используйте его

You: I'm at 41.8827, -87.6233 — what's here and is it open?

Agent: You're at Planet Fitness (a gym). It's currently open and closes
       at 11:00 PM tonight — you have about 3 hours left.

Инструменты

get_location_label

Определяет ближайшее именованное место в радиусе radius метров от заданных координат.

Параметр

Тип

По умолчанию

Описание

lat

float

обязательно

Широта (от -90 до 90)

lng

float

обязательно

Долгота (от -180 до 180)

radius

int

100

Радиус поиска в метрах (макс. 500)

Поля ответа:

Поле

Тип

Описание

place

string

null

Исходное название места из OpenStreetMap

label

string

Чистое название, готовое к отображению

category

string

null

Стабильный тип: gym, supermarket, restaurant и т. д.

distance_meters

float

null

Расстояние от ваших координат до места

is_open

bool

null

true открыто · false закрыто · null нет данных о часах работы

opens_at

string

null

Следующее время открытия HH:MM (когда закрыто)

closes_at

string

null

Время закрытия сегодня HH:MM (когда открыто)

opening_hours

string

null

Исходная строка OSM opening_hours

cached

bool

Обслуживается из 10-минутного кэша; часы работы всегда пересчитываются в реальном времени


Альтернативная установка

# pip
pip install geolabel-mcp

# run directly
GEOLABEL_API_KEY=glk_xxx geolabel-mcp

Claude Code

claude mcp add geolabel -- uvx geolabel-mcp

Затем установите свой ключ:

# add to your shell profile or .env
export GEOLABEL_API_KEY=glk_your_key_here

Конфигурация

Переменная

Обязательно

Описание

GEOLABEL_API_KEY

Да

Ваш API-ключ GeoLabel

GEOLABEL_BASE_URL

Нет

Переопределение базового URL API (по умолчанию: https://api.geolabel.dev)


Конфиденциальность

GeoLabel удаляет координаты из всех журналов сервера до того, как они попадут на диск. История перемещений не сохраняется. Данные обрабатываются в режиме реального времени и немедленно удаляются. Полная политика конфиденциальности →


Лицензия

MIT

Available Tools

1 tool
get_location_labelA

Identify a place from GPS coordinates and return its label, category, and live opening-hours status.

Use this whenever the user provides coordinates or asks what is at a location. The response gives Claude everything needed to answer location-aware questions — place name, type, whether it is open right now, and when it closes or next opens.

Args: lat: Latitude in decimal degrees (-90 to 90). lng: Longitude in decimal degrees (-180 to 180). radius: Search radius in metres. Smaller values pin to the nearest place precisely; larger values cast a wider net. Default 100 m, maximum 500 m.

Returns a dict with: place Raw venue name from OpenStreetMap (may include branch numbers or location suffixes). Prefer 'label' for display. label Clean, user-friendly name — e.g. "Walmart", "Planet Fitness", "Starbucks". Use this for display and speech. category Stable place type for logic: "gym", "supermarket", "restaurant", "fast_food", "gas_station", "pharmacy", "hospital", "cafe", "retail", etc. distance_meters Distance in metres from the supplied coordinates to the matched place centroid. is_open true → currently open. false → currently closed. null → OpenStreetMap has no hours data for this place. opens_at Next opening time as "HH:MM" (24-hour). Populated when is_open is false so you know when it reopens. null when open, or when hours are unknown. closes_at Today's closing time as "HH:MM" (24-hour). Populated when is_open is true — subtract current time to get minutes remaining. null when closed or hours unknown. opening_hours Raw OpenStreetMap opening_hours string, e.g. "Mo-Fr 09:00-18:00; Sa 10:00-17:00". null if not set in OSM. cached true if place data was served from the 10-minute in-memory cache. Hours fields are always recalculated live against the current time, even on cache hits.

ParametersJSON Schema
NameRequiredDescriptionDefault
latYes
lngYes
radiusNo

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully covers behavior: radius interpretation, caching with 10-minute TTL, live recalculation of hours, and null handling for unknown hours. It discloses all behavioral traits beyond the basic function.

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 well-structured with purpose, usage, parameters, and return fields. Every sentence adds value; no redundant or extraneous text. Front-loaded the key purpose in the first sentence.

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 no output schema, the description completely documents all return fields with explanations, including edge cases like null values. All parameters are explained. The tool's behavior (caching, live hours) is fully covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description provides detailed parameter semantics: lat/lng ranges, radius meaning with default and maximum, and concrete usage guidance. This goes far beyond the schema's minimal type information.

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 first sentence clearly states the tool identifies a place from GPS coordinates and returns label, category, and live opening-hours status. The verb 'identify' combined with the resource 'place' and specific outputs makes the purpose unmistakable.

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

Usage Guidelines5/5

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

The description explicitly says 'Use this whenever the user provides coordinates or asks what is at a location.' This direct instruction tells the agent exactly when to invoke the tool, leaving no ambiguity.

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.

  1. 1 tool updatev0.1.1
    • First observedget_location_label

TDQS

A4.8/5.0

Scored across 1 tool

Disambiguation5/5

Only one tool exists, so there is no possibility of confusion between tools. The single tool's purpose is clearly defined.

Naming Consistency5/5

With only one tool, naming consistency is inherently perfect. The name 'get_location_label' follows a clear verb_noun pattern.

Tool Count3/5

A single tool is at the low end of typical scope. It serves a focused purpose (geolocation labeling), but the server feels thin for a full MCP surface.

Completeness4/5

The tool provides rich detail (name, category, hours, distance) for its single operation. Lacks additional geolocation utilities like batch or address lookup, but core need is met.

Maintenance

ActivityInactive
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • A
    license
    B
    quality
    A
    maintenance
    Enables AI assistants to search, validate, and edit OpenStreetMap data through natural language commands and built-in safety protections. It supports discovery of nearby amenities, geographic data exploration, and secure map editing via OAuth authentication.
    31
    4
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Free geospatial MCP server for AI agents, providing geocoding, reverse geocoding, POI search, and route planning using OpenStreetMap data via Nominatim, Overpass, and OSRM.
    1
    GPL 3.0
  • A
    license
    A
    quality
    C
    maintenance
    MCP server providing structured access to OpenStreetMap data through Overpass and Nominatim APIs, enabling geocoding, nearby place searches, element queries, and tag counting without API keys.
    7
    MIT