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Here

by io.github.pipeworx-io
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Here Discover

here_discover
Read-onlyIdempotent

Find places / points of interest (restaurants, shops, landmarks, gas stations, etc.) near a location via HERE — "coffee near Times Square", "pharmacies near 48.85,2.35", "hardware stores in Austin". Returns name, category, address, coordinates, distance, and contact info. The near location can be a place name (geocoded automatically) or "lat,lng".

Input Schema

NameRequiredDescriptionDefault
nearYesPlace name (e.g. "Times Square, New York") or "lat,lng" (e.g. "40.758,-73.985") to search around.
limitNoMax results (default 10, max 50).
queryYesWhat to search for, e.g. "coffee", "pharmacy", "hardware store".
radius_kmNoOnly return places within this many km of `near` (default 100, max 1000). HERE ranks by relevance, so without this a query that matches a business NAME can return that business on another continent.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / radius_km
      Added value: +{
+  "description": "Only return places within this many km of `near` (default 100, max 1000). HERE ranks by relevance, so without this a query that matches a business NAME can return that business on another continent.",
+  "type": "number"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "near": "Times Square, New York",
+    "query": "coffee"
+  },
+  {
+    "limit": 15,
+    "near": "48.85,2.35",
+    "query": "pharmacy"
+  }
+]
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive behavior, so the safety profile is covered. The description adds real context beyond that: that a place-name `near` is geocoded automatically, and it enumerates the returned fields. It does not mention ranking quirks or rate limits, but those are handled in the schema's radius_km note.

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?

Purpose is front-loaded in the first clause, then examples, then return shape, then the near-argument rule. Every sentence carries information an agent needs and nothing is padded.

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?

There is no output schema, and the description compensates by listing the returned fields (name, category, address, coordinates, distance, contact info). Combined with the annotated safety profile and fully documented parameters, an agent has everything needed to call it correctly.

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 both required and optional parameters are already documented with examples and defaults. The description only restates the place-name-or-lat,lng duality for `near` that the schema already explains, adding no new syntax or constraint detail.

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?

States a specific verb (find) and resource (places / points of interest) with concrete scope examples like 'coffee near Times Square'. The here_* siblings (geocode, reverse_geocode, route) are clearly distinguished by the POI-search framing.

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

Usage Guidelines4/5

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

The query examples ('coffee near Times Square', 'pharmacies near 48.85,2.35') make the intended usage clear and show both accepted forms of the `near` argument. However, it never says when to prefer this over here_geocode or search_within, so there is no explicit alternative routing.

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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