Skip to main content
Glama

Data Dallas

by io.github.pipeworx-io

Dallas Query

dallas_query
Read-onlyIdempotent

Run a raw SoQL query against any Dallas open-data resource (www.dallasopendata.com) by its Socrata id (8-char like "qv6i-rri7"). Full SoQL: where/select/group/order/limit/offset. Use dallas_datasets to find a resource id, or dallas_recent for the common ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoSoQL $group.
limitNoMax rows (default 100, max 5000).
orderNoSoQL $order.
whereNoSoQL $where filter.
offsetNoRow offset for paging.
selectNoSoQL $select.
_apiKeyNoOptional — your own Socrata app token for higher rate limits. Omit to use the keyless endpoint.
resource_idYesSocrata resource id, e.g. "qv6i-rri7".

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-dallas-api-key",
+    "limit": 100,
+    "resource_id": "qv6i-rri7",
+    "where": "status = 'Open'"
+  },
+  {
+    "_apiKey": "your-data-dallas-api-key",
+    "group": "permit_type",
+    "order": "cnt DESC",
+    "resource_id": "8qv6-iprr",
+    "select": "permit_type, count(*) as cnt"
+  }
+]
  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 mark the tool as readOnlyHint and idempotentHint. The description adds that it runs raw SoQL, mentions the endpoint domain, and explains the optional _apiKey parameter for rate limits. This provides useful context beyond annotations without contradiction.

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 long, front-loading the core purpose, then adding usage tips. Every sentence is informative and non-redundant. Perfectly concise.

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?

With a full input schema (100% coverage) and no output schema, the description covers the tool's purpose, usage of parameters, and relevant siblings. It mentions the default and max limits from the schema. A minor gap: it doesn't explicitly state the return format (raw SoQL response), but that is reasonable given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the full SoQL capability and giving an example of the resource id format. It also implies which parameters are commonly used together (e.g., where, select, group, order). This goes beyond the schema descriptions.

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 explicitly states the tool runs a raw SoQL query against any Dallas open-data resource by Socrata id. It provides the resource id format (e.g., 'qv6i-rri7') and lists key SoQL clauses (where/select/group/order/limit/offset), making the purpose very clear and distinguishing it from sibling tools like dallas_datasets and dallas_recent.

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 advises using dallas_datasets to find a resource id and dallas_recent for common ones, providing alternative tools. However, it does not explicitly state when NOT to use this tool, e.g., when a simpler endpoint suffices. Still, the guidance is clear and helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Data Dallas toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with a few overlapping pairs (e.g., ask_pipeworx vs ask_pipeworx_grounded, multiple polymarket tools) that could cause mild confusion, but descriptions adequately differentiate them.

Naming Consistency3/5

Tool names consistently use snake_case, but the verb_noun pattern is not consistently applied; some names are noun_noun (dallas_datasets, bet_research) or adjective_noun (ai_visibility_check), creating a mixed nomenclature.

Tool Count2/5

With 33 tools, the server exceeds the typical well-scoped range. While the broad data domain justifies many tools, the count feels heavy and would benefit from consolidation of related functions.

Completeness4/5

The tool set covers a wide array of domains (company data, drugs, economics, prediction markets, memory, subscriptions) with only minor gaps (e.g., no direct web search tool, as ask_pipeworx mostly covers it). Overall, it is comprehensive for its purpose.

Resources