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gisgp

by io.github.uponex

generate_static_map_image

Render a GeoJSON FeatureCollection/Feature to a static PNG map image (base64 data URL) — for embedding in reports/emails/documents, unlike share_map's interactive live page. basemap: 'topo', 'streets', or 'satellite'. Reuses the exact rendering path already used inside PDF map reports, no new map-rendering logic. Optional agol_token: for a single-Point input, renders through Esri's own Static Maps Service instead (real ArcGIS basemap tiles) — uses YOUR OWN AGOL credentials/quota, not GISGP's (multi-feature/non-point input always uses the default renderer regardless of token). Returns JSON: {ok, image_data_url, feature_count, width, height, basemap}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
widthNo
accentNo#2563eb
heightNo
basemapNotopo
geojsonYes
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

A4.1/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. Explains rendering path (reuses PDF map reports logic), basemap options, and agol_token behavior for single-Point vs multi-feature input. Mentions return format. Missing error handling details, but overall transparent.

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 reasonably concise (few sentences) with a clear structure: purpose, distinction from sibling, basemap detail, token behavior, return format. Each sentence adds value, though could be slightly shorter.

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?

Given 6 parameters and an output schema (described in text), the description covers essential aspects: purpose, usage context, behavioral details, and return fields. Lacks input validation or error states, but sufficient for typical use.

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 has 0% description coverage (no parameter descriptions in JSON schema). Description adds meaning for basemap (lists options) and agol_token (explains conditional behavior), but does not detail width, height, accent, or geojson beyond stating they exist. Partial compensation.

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?

Clearly states it renders GeoJSON to a static PNG map image (base64 data URL) for embedding in reports/emails/documents, distinguishing it from share_map (interactive live page). The verb 'render' and resource 'GeoJSON FeatureCollection/Feature' are specific.

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?

Explicitly mentions when to use (embedding in reports/emails/documents) and contrasts with share_map. Provides context for optional agol_token usage, but does not specify when not to use other siblings beyond share_map.

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