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GRABOSM

OpenStreetMap MCP Server

by GRABOSM

search_pois

Find Points of Interest like restaurants, shops, and attractions within a specific area using OpenStreetMap data. Filter results by type, cuisine, or location parameters to locate nearby amenities.

Instructions

Search for Points of Interest (POIs) using Overpass API

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amenityNoAmenity type (restaurant, hospital, etc.)
shopNoShop type (supermarket, bakery, etc.)
cuisineNoCuisine type for restaurants
tourismNoTourism type (hotel, attraction, etc.)
bboxNoBounding box to search within
aroundNoSearch around a specific location
limitNoMaximum number of results (1-100, default: 10)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the Overpass API but doesn't explain rate limits, authentication requirements, response format, error conditions, or whether this is a read-only operation. For a search tool with 7 parameters and complex nested objects, this leaves significant behavioral gaps.

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 states the core purpose without unnecessary words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place.

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 (7 parameters with nested objects), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how results are structured, error handling, or performance characteristics. For a search tool in a crowded namespace of 28 siblings, more context is needed to help the agent use it effectively.

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?

The schema description coverage is 100%, providing good documentation for all parameters. The description adds no additional parameter semantics beyond what's already in the schema. This meets the baseline expectation when schema coverage is high, but doesn't enhance understanding of how parameters interact or which combinations are most effective.

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 verb ('Search for') and resource ('Points of Interest (POIs)'), and specifies the API used ('Overpass API'). However, it doesn't distinguish this tool from its many siblings like 'search_pois_smart', 'find_amenities_nearby', or 'search_by_tags', leaving the agent uncertain about when to choose this specific tool.

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 28 sibling tools including several similar search tools (search_pois_smart, find_amenities_nearby, search_by_tags, search_structured), the agent receives no help in selecting this specific POI search implementation over others.

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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