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Geoapify

by io.github.pipeworx-io

Places

places
Read-onlyIdempotent

Search for places and points of interest (POI) near a location, filtered by Geoapify category. Returns name, formatted address, categories, lat, lon, and distance from the center point. Example: places({ categories: "catering.restaurant", lat: 48.8584, lon: 2.2945, radius: 1000 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the search center in decimal degrees
lonYesLongitude of the search center in decimal degrees
limitNoMaximum number of results to return (default 20, max 100)
radiusNoSearch radius in meters (default 1000, max 50000)
_apiKeyNoOptional — your own Geoapify API key for higher limits; omit to use the shared Pipeworx key.
categoriesYesGeoapify place category (or comma-separated list), e.g. 'catering.restaurant', 'commercial.supermarket', 'accommodation.hotel'

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint. The description adds return field details and an example, enhancing transparency without contradicting annotations.

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?

Two sentences plus an example, front-loaded with purpose, no redundancy. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Describes return fields and provides an example, which is helpful given no output schema. Missing details on edge cases, but sufficient for a read-only tool with good annotations.

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

Parameters4/5

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

Schema coverage is 100% with full descriptions. The description includes an example that demonstrates parameter usage, adding practical context beyond the schema.

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 description clearly states it searches for places and POIs near a location with Geoapify category filtering, and lists return fields. This distinguishes it from siblings like geocode and reverse_geocode.

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

Usage Guidelines3/5

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

The description provides an example but no explicit guidance on when to use vs alternatives or when not to use. Usage is implied but not directed.

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

All Geoapify toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, entity_profile, compare_entities, and validate_claim, all retrieving entity data. Agents may struggle to choose correctly between them. Likewise, bet_research, polymarket_edges, and polymarket_arbitrage cover similar prediction market territory.

Naming Consistency3/5

All tool names use underscores, but the verb/noun order varies: compare_entities (verb_noun), entity_profile (noun_noun), scan_competitor_ai_presence (verb_noun), bet_research (noun_verb). Some names are overly long (scan_competitor_ai_presence). The pattern is readable but not fully consistent.

Tool Count3/5

With 31 tools, the count is high but not extreme. However, the set covers geospatial, data retrieval, prediction markets, npm scanning, and memory/feedback - too broad for a single server. Many tools feel added without clear justification, making the set feel bloated.

Completeness2/5

The geospatial subset is incomplete (missing elevation, distance matrix, isochrones). The data access tools overlap rather than form a complete API surface (e.g., no entity update/delete). Prediction market tools are numerous but redundant. The server tries to do too much and lacks depth in any area.

Resources