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gisgp

by io.github.uponex

assess_grid_exposure

Electric grid infrastructure proximity at a US point: nearby substations + transmission lines within 10 miles (community ArcGIS mirror of HIFLD data — proximity indicator, not a certified survey). No key needed. Returns JSON: {ok, substations: {count, nearest, source}, transmission_lines: {count, volt_classes, owners, source}}.

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

A3.7/5.0
Behavior4/5

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

Given no annotations, the description does a good job disclosing behavioral traits: data source (community ArcGIS mirror of HIFLD), limitations (proximity indicator, not a certified survey), and return format. It also clarifies no key is needed, implying no authentication overhead.

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 concise, front-loaded with purpose, and includes the return structure inline. Every sentence adds value, though the format could be more structured (e.g., separate sections for input constraints).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers data source, limitation, and output format but lacks details like units (miles are mentioned as radius), coordinate reference system, and how to interpret the proximity indicator. The return schema is embedded but not formally defined, leaving some gaps for an agent.

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 has 0% coverage, and the description only mentions 'at a US point' without specifying coordinate system (e.g., WGS84) or bounds for lat/lon. This leaves ambiguity for an agent selecting the tool, especially for geospatial inputs.

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 the tool assesses proximity to electric grid infrastructure (substations and transmission lines) for a point in the US within 10 miles, using a community mirror of HIFLD data. This differentiates from sibling tools like assess_renewable_site or assess_property_hazard, which focus on other aspects.

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

Usage Guidelines3/5

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

The description provides some guidance by stating 'no key needed' and indicating it's a 'proximity indicator, not a certified survey', implying use for quick screening rather than official purposes. However, it lacks explicit instructions on when to use this tool versus alternatives like assess_renewable_site.

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