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Glama

Data Calgary

by io.github.pipeworx-io

Calgary Query

calgary_query
Read-onlyIdempotent

Run a raw SoQL query against any Calgary open-data resource (data.calgary.ca) by its Socrata id (8-char like "iahh-g8bj"). Full SoQL: where/select/group/order/limit/offset. Use calgary_datasets to find a resource id, or calgary_recent for the common ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoSoQL $group (e.g. "incident_category").
limitNoMax rows (default 100, max 5000).
orderNoSoQL $order (e.g. "incident_datetime DESC").
whereNoSoQL $where filter (e.g. "incident_year=2025").
offsetNoRow offset for paging.
selectNoSoQL $select (e.g. "incident_category, count(*)").
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.
resource_idYesSocrata resource id, e.g. "iahh-g8bj" (police incidents).

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",
+    "limit": 100,
+    "resource_id": "iahh-g8bj",
+    "where": "incident_year=2025"
+  },
+  {
+    "_apiKey": "your-data-calgary-api-key",
+    "group": "incident_category",
+    "order": "count(*) DESC",
+    "resource_id": "iahh-g8bj",
+    "select": "incident_category, count(*)"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety. The description adds context on the raw SoQL nature, the full range of clauses supported, and the resource id format, which helps the agent understand the tool's behavior beyond structured hints. It does not contradict 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, front-loaded with the core purpose, and every sentence earns its place. It avoids unnecessary detail while giving essential usage pointers.

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 has no output schema and 8 parameters, the description provides enough context to invoke it correctly: how to get resource ids, the full SoQL capabilities, and the resource id format. It relies on the schema for detailed parameter limits, which is acceptable. It could be more complete by mentioning pagination or error handling, but annotations and schema cover most operational aspects.

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 provides 100% coverage with each parameter containing a description, so the baseline is 3. The description adds a little value by listing the SoQL clauses and giving the exact resource id format, but this is largely redundant with the schema's per-parameter descriptions. No meaningful additional parameter semantics are introduced.

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 runs a raw SoQL query against any Calgary open-data resource using a Socrata id. It uses a specific verb ('run') and resource ('Calgary open-data resource'), and distinguishes itself from siblings like calgary_datasets and calgary_recent by focusing on direct data querying rather than listing or retrieving common datasets.

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?

It explicitly tells the agent to use calgary_datasets to find a resource id or calgary_recent for common ones, which effectively defines when this tool should be used (when you have a specific resource id) versus when to use alternatives. This is direct and actionable.

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