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gisgp

by io.github.uponex

classify_land_cover

Land cover class at a WGS84 point via ESA CCI Land Cover 2018 (ArcGIS Living Atlas ImageServer, no key, 300m resolution). Returns JSON: {ok, class_code, class_label, source}.

NOTE 2026-07-26: gated separately (mcp_layer1_landcover, Off pending live
smoke-check) — swapped from the earlier ESA WorldCover WMS source, which
was confirmed dead (being phased out). This ArcGIS REST identify endpoint
was live-verified locally (Sofia -> class 8, "Artificial Surface or
Urban Area") before this swap.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Added

TDQS

A3.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses data source, resolution (300m), coordinate system (WGS84), return format (JSON with specific fields), and current operational status (gated, off pending smoke-check). This gives good insight into tool behavior and limitations.

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

Conciseness3/5

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

The description is front-loaded with the main purpose, but includes a lengthy note about source swap and status. While informative, this extra detail could be separated or shortened. Not overly verbose but not maximally concise.

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?

For a simple point query tool with an output schema (not shown), the description covers key aspects: what it does, data source, resolution, return format, and current operational status. This is sufficient for an agent to understand and invoke the tool 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 coverage is 0%, so description must compensate. It adds meaning by specifying that the point is in WGS84 and that lon/lat are used, but does not detail ranges, validation, or order. Partial compensation, not exhaustive.

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 classifies land cover at a WGS84 point using a specific data source (ESA CCI Land Cover 2018). It includes verb (classify), resource (land cover), and coordinates. It distinguishes from siblings by specifying the exact classification task, which is unique among the listed sibling tools.

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

Usage Guidelines2/5

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

The description does not explicitly state when to use this tool versus alternatives. It provides context about the source status (gated, off pending check) but no guidance on when it is appropriate or what other tools might be used for similar tasks.

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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