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Glama

Mapbox

by io.github.pipeworx-io

Geocode Reverse

geocode_reverse
Read-onlyIdempotent

"What's at [lat,lng]" / "reverse geocode coordinates" / "what address is at these coords" / "what place is at this GPS point" — convert longitude / latitude into the nearest street address, neighborhood, city, region, or country via Mapbox's global geocoder. Works worldwide.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes
limitNo
typesNo
countryNo
languageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / examples
      [
  {
    "lat": 40.7128,
    "lon": -74.006
  },
  {
    "country": "FR",
    "lat": 48.8584,
    "limit": 3,
    "lon": 2.2945
  }
]
    • changedOutput schema / (root)
      Before
      null
      After
      {
  "description": "Mapbox Geocoding API response for reverse geocoding",
  "type": "object"
}
  2. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by disclosing behavioral details: it returns the 'nearest' result via Mapbox, works globally, and can yield various geographic granularities. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with helpful natural language aliases. It is front-loaded and efficient, though the list of example queries is slightly redundant and could be trimmed without losing meaning.

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?

The tool has an output schema and safe-read annotations, so the description doesn't need to explain return values. It covers global scope and result types, but misses semantic details for optional parameters. The schema examples partially offset this gap.

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

Parameters2/5

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

Schema description coverage is 0%, and the description only references latitude and longitude implicitly. Optional parameters like limit, types, country, and language are not explained at all, leaving the agent to guess their meaning from the schema examples alone.

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 the tool converts latitude/longitude into the nearest address, neighborhood, city, region, or country. It distinguishes itself from the sibling 'geocode_forward' by explicitly calling 'reverse geocode' and providing natural language examples that align with the tool's direction.

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?

Usage context is well implied through example queries like 'What's at [lat,lng]' and 'reverse geocode coordinates'. It does not explicitly mention alternatives or exclusions, but the purpose is unique relative to sibling tools and the description makes when-to-use obvious.

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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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) and several tools serve similar data-retrieval functions, making it difficult for an agent to distinguish which to use.

Naming Consistency4/5

Tool names mostly follow a consistent verb_noun pattern (e.g., geocode_forward, generate_llms_txt, resolve_entity). A few less descriptive names (forget, recall) exist but overall naming is predictable.

Tool Count2/5

38 tools is far too many for a server branded as 'Mapbox'. Only about 8 tools directly relate to map/geospatial functionality; the rest are unrelated (Pipeworx data, Polymarket, memory). The scope is dramatically overextended.

Completeness2/5

The Mapbox-specific tools lack coverage of major features like style management, tilesets, or data upload. The non-Mapbox tools cover their domains moderately, but the server's overall completeness for its named purpose (Mapbox) is severely lacking.

Resources