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gisgp

by io.github.uponex

geocode_address

Forward-geocode a free-text address to lon/lat. Default: OSM Nominatim (no key, free, fair-use rate limited) — the complement to analyze_location's reverse geocode. Optional agol_token: route through Esri's own World Geocoding Service instead for more authoritative matches — uses YOUR OWN AGOL credentials/quota, not GISGP's (no extra charge either way, no GISGP account needed for this option). Returns JSON: {ok, lon, lat, display_name, type, importance, source}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYes
agol_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / agol_token
      Added value: +{
+  "default": "",
+  "title": "Agol Token",
+  "type": "string"
+}
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

No annotations provided, so description carries full burden. It discloses provider behavior (rate limits, free), credential needs, and return format. Explains that agol_token routes through Esri's service with user's own quota. No contradictions.

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?

Description is slightly verbose but well-structured: core function first, then details, then return format. Could be trimmed slightly but every sentence adds value.

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?

Tool complexity is moderate. Output schema exists and description lists return fields. Parameter semantics, behavioral notes, and usage scenarios are fully covered. Complete for effective use.

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 description coverage is 0%, so description must add meaning. It does: 'address' is free-text; 'agol_token' is optional and explained. Both parameters are covered beyond just names and types.

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?

Description clearly states it forward-geocodes a free-text address to lon/lat. Explicitly distinguishes itself as complement to sibling analyze_location's reverse geocode, which differentiates well.

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?

Describes two usage paths: default OSM Nominatim (free, rate-limited) and optional agol_token for Esri service. Notes no extra charge and that agol_token uses user's own credentials/quota. Does not explicitly list when not to use, but adequate context.

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.

Resources