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Glama

Arcgis Vilas

by io.github.pipeworx-io

Query Layer

query_layer
Read-onlyIdempotent

Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like where, comma-separated out_fields, order_by, limit, offset. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFeature/Map Service layer url ending in /FeatureServer/<n> or /MapServer/<n>.
limitNoMax features (1-2000, default 50).
whereNoSQL where clause, e.g. "STATE = 'CA' AND YEAR >= 2020". Default "1=1".
offsetNoPagination offset.
order_byNoe.g. "POP DESC".
out_fieldsNoComma-separated field names, or "*" for all (default).

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 50,
+    "out_fields": "*",
+    "url": "https://gis.vilas.wi.us/arcgis/rest/services/Parcels/FeatureServer/0",
+    "where": "1=1"
+  },
+  {
+    "limit": 100,
+    "out_fields": "ADDRESS,CITY,ZIP",
+    "url": "https://gis.vilas.wi.us/arcgis/rest/services/Addresses/FeatureServer/0",
+    "where": "CITY = 'Eagle River'"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that it returns 'attribute rows (and geometry)' and explains pagination with limit/offset, providing useful behavioral context beyond annotations.

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 two sentences: the first efficiently lists all key parameters and return, the second provides a practical tip. No fluff, front-loaded with purpose.

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

Completeness5/5

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

For a 6-parameter query tool with no output schema, the description covers purpose, parameters, return type, and usage tip. It references prerequisite workflow and assumes ArcGIS knowledge, which is appropriate given the domain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so baseline is 3. The description adds examples, default values for where and out_fields, and explains SQL-like syntax for where/order_by, which adds significant value beyond the schema.

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 queries an ArcGIS Feature/Map Service layer by URL with SQL-like parameters, distinguishing it from siblings like layer_info (metadata) and search_datasets (finding datasets). The verb 'query' and resource 'layer' 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?

The description mentions 'from search_datasets', establishing a workflow context. It provides examples and defaults, but does not explicitly compare to alternatives like layer_info or state when not to use it. Still, usage is clearly implied.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical data routers, while polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, and polymarket_edge_tracker all target prediction-market opportunities with subtle distinctions. An agent can easily select the wrong one for a given task, especially when tool descriptions emphasize similar use cases.

Naming Consistency3/5

Many tools follow a verb_noun pattern (ask_pipeworx, query_layer, search_datasets, validate_claim), but several break it (entity_profile, layer_info, recent_changes, polymarket_edges). Consistent prefixes like pipeworx_ and polymarket_ help orientation, yet the overall style is a mix of verb phrases, noun phrases, and compound names.

Tool Count2/5

34 tools is excessive for a server named 'Arcgis Vilas' whose actual GIS capabilities are only three tools (search_datasets, query_layer, layer_info). Bundling unrelated functionality like Polymarket betting, memory, subscriptions, npm scanning, and AI visibility checks inflates the count without advancing the server's apparent core purpose.

Completeness3/5

For the ArcGIS domain implied by the server name, the surface is severely incomplete—only search, layer schema, and attribute queries are provided, with no editing, spatial analysis, or geocoding. If the domain is instead interpreted as a general data-access toolkit, coverage is quite broad, but the tool set doesn't align with the declared server name, and even then there are gaps like missing write/update operations.

Resources