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GRABOSM

OpenStreetMap MCP Server

by GRABOSM

find_amenities_nearby

Locate nearby amenities like restaurants, shops, or services around a specific geographic point using OpenStreetMap data.

Instructions

Find amenities near a specific location

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude
lonYesLongitude
radiusNoSearch radius in meters (default: 1000)
amenity_typeNoSpecific amenity type to search for
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 finds amenities but lacks details on what constitutes an 'amenity', how results are returned (e.g., format, pagination), rate limits, authentication needs, or error handling. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 with zero waste. It is front-loaded with the core purpose and appropriately sized for a straightforward search tool, making it easy for an agent to parse quickly.

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 moderate complexity (4 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, result limitations, or error conditions, which are critical for an agent to use the tool effectively. Without annotations or an output schema, the description should provide more context to compensate.

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%, so the schema fully documents all parameters (lat, lon, radius, amenity_type). The description adds no meaning beyond what the schema provides, such as examples of amenity types or clarification on coordinate systems. 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Find') and resource ('amenities'), specifying the location-based nature ('near a specific location'). It distinguishes itself from most siblings by focusing on amenities rather than routes, distances, or OSM data operations, though it doesn't explicitly differentiate from similar tools like 'search_pois' or 'search_pois_smart'.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools available for location-based searches (e.g., 'search_pois', 'search_pois_smart', 'search_location'), the description offers no context on preferred use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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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