Count features in an ArcGIS FeatureServer layer, optionally filtered by a WHERE clause.
service_url: full layer URL ending in /FeatureServer/<n>. token: only for private layers.
Returns JSON: {"ok": true, "count": ..., "name": ..., "geometry": ...}.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | ||
| where | No | 1=1 | |
| service_url | 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?
No annotations are provided, so the description carries full burden. It discloses the return JSON structure and notes that token is only for private layers, but does not mention rate limits, error handling, or behavior on unavailable services. The description offers basic transparency but lacks depth.
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 three sentences, front-loading the purpose. It is efficient but could be more structured (e.g., using bullet points for parameters). No wasted words.
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?
Given the simple tool (count, 3 parameters, output schema described), the description covers the essential aspects. Sibling tools are many but distinct enough that the core function is clear. However, for a counting tool, the description could mention if count is approximate or exact.
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?
With 0% schema description coverage, the description compensates well: it explains service_url format, token purpose, and where defaults. However, it does not detail the token's usage (e.g., how to obtain it) or the WHERE clause syntax beyond a default.
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 uses a specific verb ('count') and resource ('features in an ArcGIS FeatureServer layer'), with optional WHERE filtering. It clearly distinguishes from sibling tools like query_features (which returns features) and query_statistics (which computes aggregates).
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 implies use for counting features with optional filtering, but does not explicitly state when to use this tool over alternatives. It provides no 'when not to use' guidance or comparisons to sibling tools.
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.