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rteina

geoparquet-mcp

by rteina

geoparquet_find_nearest

Find the nearest features to a point, sorted by distance with great-circle kilometers. Specify a center coordinate and radius to get the closest matches within that area.

Instructions

Return the features closest to a point, nearest first, each with its great-circle distance in kilometres.

WHEN TO USE IT. For "what is near here" and "which is the closest" — the questions where the ranking and the distance are the answer. Use geoparquet_filter_spatial instead when you want everything in an area rather than the closest few.

HOW IT STAYS CHEAP. A radius is not something Parquet statistics can prune on, so the search circle is first widened to its bounding rectangle, which is prunable; the exact distance is then computed only over the rows that survive, and used both to filter and to order. A large radius therefore costs a large read: prefer the smallest radius that can contain the answer, and widen it only if you come back empty.

PARAMETERS. source: dataset name. lon, lat: the centre point, in WGS 84 degrees. Longitude first. radius_km: how far to look, up to 500. Results outside it are excluded, so this is a filter, not just a hint. category, name_contains: the same narrowing as geoparquet_filter_spatial. columns: column expressions to return. limit: how many neighbours, capped at 1000.

WHAT COMES BACK. rows, ordered nearest first, each carrying distance_km; the search_bbox actually used for pruning; and the scan block.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes
limitNo
sourceNooverture_places
columnsNo
categoryNo
radius_kmNo
name_containsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so richly: it explains the radius acts as a filter, not a hint; distances are great-circle in kilometres; results are ordered nearest first; the search_bbox is used for pruning; and cost characteristics are disclosed ('A large radius therefore costs a large read'). This goes far beyond basic operation.

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?

Though lengthy, the description is organized into clear labeled sections (purpose, when to use, cost behavior, parameters, return values) with no filler. Each sentence conveys essential operational information, such as the bounding-rectangle pruning strategy and the exact response shape.

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?

Given 8 parameters, no annotations, and the presence of an output schema, this description is complete. It explains what to pass, how the tool behaves, what the output contains (rows with distance_km, search_bbox, scan block), and how to choose between this and sibling tools. Nothing critical for correct invocation is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate entirely. It does: every parameter is explained with added meaning — 'lon, lat' are WGS 84 degrees with longitude first, radius_km is capped at 500 and is a hard filter, limit is capped at 1000, and category/name_contains are stated to behave like the sibling filter tool.

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 opens with a precise verb and resource: 'Return the features closest to a point, nearest first, each with its great-circle distance in kilometres.' This clearly distinguishes it from sibling tools like geoparquet_filter_spatial, which returns everything in an area rather than the closest few.

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

Usage Guidelines5/5

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

An explicit 'WHEN TO USE IT' section states the suitable question types ('what is near here' and 'which is the closest') and names the exact alternative: 'Use geoparquet_filter_spatial instead when you want everything in an area rather than the closest few.' This gives the agent direct routing guidance.

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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