Skip to main content
Glama
BACH-AI-Tools

Geodb Cities MCP Server

cities_near_division

Find cities near any administrative division worldwide, with filters for population, distance, country, time zone, and name to locate specific urban areas.

Instructions

Get cities near the given administrative division, filtering by optional criteria.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typesNoOnly cities for these types (comma-delimited): CITY | ADM2
radiusYesThe location radius within which to find cities100
distanceUnitNoThe unit of distance to use: MI | KM
countryIdsNoOnly cities in these countries (comma-delimited country codes or WikiData ids)
excludedCountryIdsNoOnly cities NOT in these countries (comma-delimited country codes or WikiData ids)
timeZoneIdsNoOnly cities in these time-zones
minPopulationNoOnly cities having at least this population0
maxPopulationNoOnly cities having no more than this population0
namePrefixNoOnly cities whose names start with this prefix. If languageCode is set, the prefix will be matched on the name as it appears in that language.
namePrefixDefaultLangResultsNoExample value:
languageCodeNoDisplay results in this language
asciiModeNoExample value:
hateoasModeNoExample value:
includeDeletedNoWhether to include any cities marked deleted: ALL | SINCE_YESTERDAY | SINCE_LAST_WEEK | NONE
limitNoThe maximum number of results to retrieve0
offsetNoThe zero-ary offset into the results0
sortNoHow to sort the results. Format: ±SORT_FIELD,±SORT_FIELD where SORT_FIELD = countryCode | elevation | name | population
divisionIdYesExample value: Q104994
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. The description only states what the tool does ('Get cities...') without mentioning any behavioral traits such as rate limits, authentication requirements, error handling, or response format. For a tool with 18 parameters and no output schema, this lack of behavioral context is a significant gap, leaving the agent uncertain about how the tool operates beyond basic functionality.

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 front-loads the core purpose without unnecessary elaboration. It uses clear language and avoids redundancy, making it easy to parse. Every word serves a purpose, adhering to the principle that each sentence should earn its place, resulting in an optimally concise and well-structured description.

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?

Given the tool's complexity (18 parameters, no output schema, and no annotations), the description is insufficiently complete. It lacks details on behavioral traits, usage guidelines relative to siblings, and output expectations. While the schema covers parameters, the description doesn't compensate for the absence of annotations or output schema, leaving significant gaps in understanding how to effectively use this tool in context.

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?

Schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds minimal value beyond the schema by mentioning 'filtering by optional criteria,' which aligns with the many filter parameters in the schema. However, it doesn't provide additional context on parameter interactions or usage examples, so it meets the baseline score of 3 where 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: 'Get cities near the given administrative division, filtering by optional criteria.' It specifies the verb ('Get'), resource ('cities'), and scope ('near the given administrative division'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'places_near_location' or 'admin_divisions_near_division,' which could cause confusion about when to use this specific tool versus alternatives.

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 mentions 'filtering by optional criteria' but doesn't specify scenarios or prerequisites for its use. With sibling tools like 'places_near_location' and 'admin_divisions_near_division' available, the lack of differentiation leaves the agent without clear usage context, potentially leading to incorrect tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BACH-AI-Tools/bachai-geodb-cities'

If you have feedback or need assistance with the MCP directory API, please join our Discord server