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gisgp

by io.github.uponex

export_geojson_to_pdf

PAID (150 credits) — render an ad-hoc GeoJSON FeatureCollection to a one-page PDF report (static map + property table, base64-encoded PDF). Separate from the web app's own PDF Builder (AGOL-service-tied, quota- gated there) — this is for GeoJSON an agent already has in hand. Requires Authorization: Bearer and sufficient credits balance. Returns JSON: {ok, pdf_base64, feature_count, truncated, size_bytes}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoGISGP GeoJSON Export
accentNo#2563eb
geojsonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses credit cost, authentication requirement, output format (base64-encoded PDF), return schema (ok, pdf_base64, feature_count, truncated, size_bytes), and that it produces one page with map and table. It does not detail error handling or validation, but covers key behavioral traits.

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 is a single, well-structured sentence packed with essential information: cost, purpose, differentiation, prerequisites, and output format. Every part adds value, and it is front-loaded with the cost to set expectations.

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 the tool's complexity (paid, auth, output schema), the description covers most needs: purpose, alternatives, auth, credits, return fields. However, it omits details like maximum features, meaning of 'truncated', and parameter explanations, leaving minor gaps.

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 coverage is 0%, so the description must compensate. It implies the geojson parameter by referencing 'GeoJSON FeatureCollection' but does not explain the 'title' or 'accent' parameters. Their defaults are given in the schema, but meaning (e.g., accent is a color) is left unclear for the agent.

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's purpose: rendering an ad-hoc GeoJSON FeatureCollection to a one-page PDF report (static map + property table, base64-encoded). It explicitly distinguishes this from the web app's PDF Builder, which is tied to AGOL services and quota-gated, clarifying when to use this tool versus alternatives.

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 provides explicit guidance: use this for GeoJSON the agent already has in hand, not for AGOL-service-tied data. It also lists prerequisites (Authorization: Bearer, sufficient credit balance) and mentions the cost (150 credits), helping the agent decide when to invoke.

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