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Glama

Arcgis Glasgow

by io.github.pipeworx-io

Search Datasets

search_datasets
Read-onlyIdempotent

Search Glasgow City Council GIS open geospatial datasets (parcels, zoning, public works & city services) by keyword. Returns each dataset's name, summary, record_count, owner/org, and its Feature Service url — pass that url to query_layer / layer_info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-50, default 20).
queryNoKeyword(s), e.g. "parcels", "crime", "flood zones".
org_idNoOptional ArcGIS orgId to override the default (Glasgow City Council GIS).

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: +[
+  {
+    "query": "parcels"
+  },
+  {
+    "limit": 10,
+    "query": "flood zones"
+  }
+]
  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, idempotentHint, and non-destructive hints, so the safety profile is covered. The description adds value by listing the exact return fields (name, summary, record_count, owner/org, Feature Service URL), which tells the agent what to expect, and clarifies that results are open geospatial datasets.

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?

Two sentences with no filler: the first states the action and scope, the second lists return fields and the next-step workflow. Every clause earns its place.

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 search tool with no output schema, the description covers purpose, input scope, return structure, and follow-up action. It lacks explicit handling for edge cases like pagination or empty results, but given the simple parameter set, this is a complete enough description.

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?

The input schema already provides 100% coverage, describing query, limit, and org_id with examples. The description's mention of keyword search aligns with the query parameter but adds no new syntax or format details 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 identifies the tool as a search over Glasgow City Council GIS open geospatial datasets by keyword, listing specific dataset categories. It also distinguishes itself from sibling tools by noting that the returned Feature Service URL should be passed to query_layer/layer_info, making its role in the workflow explicit.

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 downstream guidance: after finding a dataset, pass its URL to query_layer or layer_info. This positions search_datasets as the discovery step, with clear context on when to use it versus the sibling tools that operate on a specific dataset.

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

A3.6/5.0
Disambiguation2/5

Several tools have unclear boundaries: ask_pipeworx, ask_pipeworx_beta (currently functionally identical), ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all route to the same underlying catalog with only subtle differences. The Polymarket cluster (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) also substantially overlaps in purpose, and the two unrelated domains (GIS vs. data/betting) make it worse.

Naming Consistency3/5

Names are readable and form some predictable clusters (polymarket_* prefix, ask_pipeworx_* suffixes, subscribe/unsubscribe/list_subscriptions), but conventions are mixed: bare verbs (remember, forget, recall), noun_noun (layer_info, entity_profile, pipeworx_feedback), verb_noun (query_layer, search_datasets), and adjective_noun (deep_research, recent_alerts). No single pattern dominates, though nothing is chaotic.

Tool Count2/5

34 tools is well above the 25+ threshold for a heavy surface, and the count is not justified by the server's stated identity: only 3 of 34 tools (search_datasets, layer_info, query_layer) relate to ArcGIS Glasgow. The remaining 31 tools belong to several unrelated domains (Pipeworx data querying, Polymarket betting, AI visibility, memory, npm scanning), making the effective scope far too broad.

Completeness2/5

For the server's named ArcGIS Glasgow domain, the surface is thin: search, schema inspection, and query are present, but there is no way to list all datasets, no spatial querying, and no write/update capability. Meanwhile the 31 non-GIS tools create a sprawling second server's worth of functionality, so the set as a whole has no coherent domain whose coverage can be judged complete.

Resources