Convert a Shapefile ZIP (base64-encoded .zip with .shp/.dbf/.shx[/.prj]) directly to GPX — points become waypoints, lines/polygons become tracks (2026-09-03). Returns GPX 1.1 XML as plain text.
| Name | Required | Description | Default |
|---|---|---|---|
| shapefile_zip_base64 | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and discloses the key behaviors: points become waypoints, lines/polygons become tracks, and output is GPX 1.1 XML as plain text. It does not state edge-case behavior (e.g., CRS handling, attribute preservation, unsupported geometry types), but the core conversion profile is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the verb and resource, and each clause adds either input constraints or output behavior. The parenthetical date (2026-09-03) is unexplained and slightly extraneous, but the overall structure remains tight.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter converter with an output schema, the description covers the input contract, the conversion mapping, and the return format, leaving little ambiguity. Minor omissions like CRS handling and attribute preservation are not critical for correct invocations at this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines shapefile_zip_base64 as a string with no description, so the description entirely compensates by specifying the expected encoding (base64), container (.zip), and required member files (.shp/.dbf/.shx, optional .prj). This gives the agent everything needed to construct the parameter correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the precise action (convert Shapefile ZIP to GPX), defines the accepted container format (base64-encoded .zip with .shp/.dbf/.shx[/.prj]), and specifies geometry mapping rules. This clearly distinguishes it from sibling converters like geojson_to_gpx or kml_to_gpx.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the input condition unambiguous: it is for base64-encoded Shapefile ZIPs, which implies when to select it over format-specific siblings. It does not explicitly name alternatives or exclusions, but the precise input format provides enough context for an agent to route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.