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Glama

Data Austin

by io.github.pipeworx-io

Austin Query

austin_query
Read-onlyIdempotent

Run a raw SoQL query against any Austin open-data resource (data.austintexas.gov) by its Socrata id (8-char like "fdj4-gpfu"). Full SoQL: where/select/group/order/limit/offset. Use austin_datasets to find a resource id, or austin_recent for the common ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoSoQL $group.
limitNoMax rows (default 100, max 5000).
orderNoSoQL $order (e.g. "occ_date_time DESC").
whereNoSoQL $where filter.
offsetNoRow offset for paging.
selectNoSoQL $select (e.g. "crime_type, count(*)").
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.
resource_idYesSocrata resource id, e.g. "fdj4-gpfu" (crime reports).

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-austin-api-key",
+    "group": "crime_type",
+    "resource_id": "fdj4-gpfu",
+    "select": "crime_type, count(*)",
+    "where": "occ_date_time > '2024-01-01'"
+  },
+  {
+    "_apiKey": "your-data-austin-api-key",
+    "limit": 100,
+    "order": "inspection_date DESC",
+    "resource_id": "wvfd-dwi5"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. Description adds context about the Socrata endpoint and raw SoQL syntax but does not discuss rate limits or side effects beyond that. Adds some value but limited.

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?

Description is three sentences, front-loaded with core purpose, lists clauses, and directs to sibling tools. No wasted words.

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 8 parameters and no output schema, description explains the tool's purpose, syntax, and discovery path. Could mention return format, but not essential for this tool type.

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 coverage is 100% with descriptions for all 8 parameters. Description adds high-level context (e.g., resource_id format, optional _apiKey) but does not significantly deepen understanding beyond 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?

Description clearly states it runs a raw SoQL query against Austin open-data resources, specifies resource ID format, and lists supported clauses. It distinguishes from sibling tools austin_datasets and austin_recent by directing users to those for discovery.

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?

Description explicitly says to use this tool for SoQL querying and mentions sibling tools for finding resource IDs. It does not provide explicit when-not-to-use guidance, but context is clear.

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

A4/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as multiple ask_pipeworx variants (beta, grounded) and several prediction market tools (arbitrage, edges, fill risk, spread). While descriptions help differentiate them, the abundance of similar tools makes it easy for an agent to misselect.

Naming Consistency3/5

Tool names are a mix of snake_case with inconsistent prefixes: some use 'ask_', 'polymarket_', 'austin_', while others are isolated verbs (forget, remember) or compound nouns (entity_profile). The pattern is not uniform but still readable.

Tool Count3/5

With 34 tools, the server is heavy. Although each tool seems justified for its niche, the set could be consolidated (e.g., merging ask_pipeworx variants) to reduce clutter. The count feels slightly excessive for the scope.

Completeness4/5

The server covers a broad range of domains: Austin open data, pipeworx data, prediction markets, memory management, and subscriptions. Core workflows are well-supported, with only minor gaps like a missing cross-source search tool.

Resources