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gisgp

by io.github.uponex

bundle_geocode_enrich

PAID (30 credits PER ADDRESS, max 10 addresses/call) — batch geocode + enrich. For each address: forward-geocodes to lon/lat (free fallback chain: OSM Nominatim -> Photon -> US Census), then reverse-geocodes for country/region/locality context and classifies land cover at that point. Replaces 3 separate calls per address: geocode_address + analyze_location + classify_land_cover. Use estimate_cost(tool_name= "bundle_geocode_enrich", units=) first to quote. Requires Authorization: Bearer and sufficient credits balance.

Returns JSON: {ok, results: [{address, ok, lon, lat, display_name,
geocode_source, country, region, locality, land_cover} or
{address, ok:false, error}], evaluated, failed_count}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Added

TDQS

A4.8/5.0
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It transparently discloses the paid nature (30 credits per address), the auth requirement and credit balance precondition, and the fallback geocoding chain. It also specifies the JSON return structure with failed_count, but it doesn't explicitly state that it is read-only or idempotent, which is implied but not spelled out.

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 opens with a prominent 'PAID' warning and then packs a clear functional summary, alternative naming, usage prerequisite, and return format into a tight set of sentences. Every sentence earns its place; there is no filler or redundancy.

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?

This is a complete description: it covers purpose, cost, auth, per-call limits, alternatives, prerequisite estimation, and a detailed return schema. With an output schema also present, the description goes beyond the minimum and anticipates agent needs, leaving no critical gaps for a paid, multi-step tool.

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?

The input schema only says 'addresses' is an array of strings with no description (0% coverage). The description compensates thoroughly by explaining each element is an address, capping at 10 per call, and linking the count to estimate_cost's 'units' parameter. This adds meaning well beyond the schema's raw type definition.

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 performs batch geocoding and enrichment, detailing the exact pipeline (forward geocode to lon/lat, reverse geocode for context, and land cover classification). It differentiates from sibling tools by explicitly naming geocode_address, analyze_location, and classify_land_cover as the three separate calls it replaces, making its scope unmistakable.

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?

The description says 'Replaces 3 separate calls per address' and advises to 'Use estimate_cost(tool_name=... ) first to quote,' which is explicit, actionable guidance. It also communicates the limit of 10 addresses per call and the per-address cost, helping an agent decide when to invoke this bundle versus simpler alternatives.

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

B3.3/5.0
Disambiguation2/5

Many assess_* composite tools (datacenter, ev_charging, renewable, telecom, due_diligence) share the same building blocks of grid proximity, land cover, and terrain, making their boundaries fuzzy. assess_property_hazard_x402 also duplicates assess_property_hazard with only a payment-method difference, and bundle_* tools intentionally overlap with the free primitives they replace.

Naming Consistency3/5

There is a mix of verb_noun tools (query_features, geocode_address), noun-first geometry tools (centroids_geojson, envelope_geojson), and inconsistent _geojson suffix usage (buffer_geojson, fix_geometry, geometry_stats). The assess_* and bundle_* prefixes offer some grouping, but no single naming pattern is followed across the set.

Tool Count1/5

With 85 tools, the surface is extreme for an MCP server and far exceeds the typical well-scoped 3-15 range. Many tools are convenience bundles or variants that could be consolidated, making the count a significant usability burden.

Completeness4/5

The toolkit covers a broad range of GIS tasks: format conversions, GeoJSON analysis, FeatureServer query/inspection, geocoding, site assessment, and sharing. Minor gaps exist (e.g., no Excel-to-GeoJSON, no FeatureServer update/delete), but most missing functionality can be worked around by chaining existing tools.

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