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Data Calgary

by io.github.pipeworx-io

Calgary Datasets

calgary_datasets
Read-onlyIdempotent

Search the Calgary open-data catalogue (data.calgary.ca) for datasets by keyword. Returns dataset names, descriptions, and Socrata resource ids to use with calgary_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-100, default 20).
queryNoKeyword(s), e.g. "parking", "housing", "tree".
offsetNoOffset for paging.
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.

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: +[
+  {
+    "_apiKey": "your-data-calgary-api-key",
+    "query": "parking"
+  },
+  {
+    "_apiKey": "your-data-calgary-api-key",
+    "limit": 50,
+    "query": "tree housing"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds that results include dataset names/descriptions/resource ids, which is useful return-value context but lacks deeper behavioral detail like pagination or auth nuances. 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?

One compact sentence captures purpose, resource, and return value without waste. It is front-loaded and every clause contributes meaning.

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 no output schema, the description does well to list return fields. It also connects to calgary_query. It lacks explicit mention of pagination or rate limits, but those are covered by schema parameter descriptions, so the description is largely 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?

Schema description coverage is 100%, so parameters are already self-explanatory. The description adds nothing about parameter syntax or formats beyond the schema, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Search') and names the exact resource ('Calgary open-data catalogue'). It also states the return payload (dataset names, descriptions, Socrata resource ids), which clearly distinguishes it from sibling tools like calgary_recent and calgary_query.

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 explains that returned resource ids are for use with calgary_query, providing clear 'next-step' guidance. It doesn't explicitly exclude other tools or mention calgary_recent, but the keyword-search workflow is well 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

A4.3/5.0
Disambiguation4/5

Most tools have distinct purposes, but there are overlapping families (ask_pipeworx variants, company research tools) that could cause confusion. Descriptions help differentiate, but an agent might misselect without careful reading.

Naming Consistency4/5

Tools follow snake_case with a verb+noun pattern, but some names are less clear (e.g., 'recall', 'remember' are verbs alone). Overall consistent enough, with minor deviations.

Tool Count4/5

33 tools is on the higher side, but the server covers a wide domain (data retrieval, prediction markets, monitoring). Each tool has a clear purpose, so the count feels appropriate rather than excessive.

Completeness5/5

The tool surface is remarkably complete: querying, comparisons, monitoring, alerts, memory, arbitrage, edge tracking. There are no obvious gaps for the intended data analytics and prediction market use case.

Resources