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Glama

Arcgis Carlsbad

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://services.arcgis.com/sharing/rest/content/items/.../FeatureServer/0",
+    "where": "1=1"
+  },
+  {
+    "limit": 100,
+    "order_by": "ACRES DESC",
+    "out_fields": "PARCEL_ID,ZONE_CODE,ACRES",
+    "url": "https://services.arcgis.com/sharing/rest/content/items/.../FeatureServer/1",
+    "where": "ZONE_CODE = 'RES'"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavioral value by specifying that the tool returns attribute rows and geometry, and that the query is SQL-like with configurable parameters. It does not mention authentication or rate limits, but for a read-only public data query tool this is sufficient; no contradiction with 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 three sentences, with the first sentence stating the purpose, the second listing the key parameters, and the third offering a concrete usage example. It is front-loaded, concise, and every sentence contributes value. No filler or redundancy.

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 simplicity and the rich annotations/schema, the description covers the necessary context: what it queries, the URL source, the SQL-like parameters, and the return type. It lacks explicit detail on pagination semantics or output format, but these are partially covered by the schema and are not critical for a read-only query tool. Overall, it is sufficiently complete.

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?

All six parameters are fully described in the input schema (100% coverage), so the description's mere list of parameter names adds little semantic value. The schema already explains each parameter's format and defaults. The description's only additional enhancement is the sampling tip for where/out_fields, which provides a small usage pattern 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 core action: 'Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets)'. It uses a specific verb ('Query') and identifies the resource type, distinguishing it from sibling tools like search_datasets (which finds datasets) and layer_info (which presumably returns metadata). The mention of returning attribute rows and geometry further clarifies its purpose.

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?

Provides practical context by noting the URL comes from search_datasets and suggesting a sampling pattern (where="1=1" + out_fields="*"). However, it does not explicitly mention when to use this instead of alternatives like layer_info or search_within, nor does it state any exclusions. This is clear usage context but lacks direct alternative guidance.

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

A3.5/5.0
Disambiguation2/5

Several tools have overlapping purposes, e.g., multiple 'ask' tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and multiple 'compare' tools (compare_entities, scan_competitor_ai_presence). Descriptions are verbose but often don't clearly distinguish when to use each, causing confusion.

Naming Consistency1/5

Naming is highly inconsistent: snake_case (ai_visibility_check), camelCase (polymarket_fill_risk), and arbitrary prefixes (scan_, generate_, etc.). No consistent verb_noun pattern; e.g., 'query_layer' vs 'search_datasets' vs 'layer_info' all involve data retrieval but use different patterns.

Tool Count2/5

33 tools is excessive for a server purportedly focused on ArcGIS Carlsbad. Many tools are unrelated (e.g., polymarket betting, npm package scanning). The core ArcGIS functionality could be covered by 3-5 tools, but the server is bloated with Pipeworx utilities.

Completeness3/5

The ArcGIS portion lacks update/delete capabilities and is limited to querying. The Pipeworx tools cover a broad range of data sources but introduce many dependencies and meta-tools, creating a cluttered surface with dead ends (e.g., tools requiring paid accounts without fallback).

Resources