Houston Open Data MCP

List Houston topic groups

houston_list_groups

Read-onlyIdempotent

List Houston Open Data topic groups with dataset counts, then use a group name to filter searches for relevant city datasets.

Instructions

List the portal's topic groups and their dataset counts.

Use a group's name as the group filter in houston_search_datasets.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "houston_list_groups"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 6, 2026

TDQS

A4.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered. The description adds only that dataset counts are included, plus the follow-on filter usage; it says nothing about scoping or completeness of the returned list beyond what the output schema supplies.

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 short sentences, purpose first and the actionable cross-reference second, with no redundant restatement of the title or annotations. Every sentence earns its place.

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 zero parameters, rich annotations and an output schema, the description carries only what structured fields cannot: what the list contains and how to use the names downstream. The only minor gap is that it does not say whether the result is scoped to a workspace or organization.

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?

The tool takes no parameters, so the parameter baseline of 4 applies. The description correctly implies a no-argument call and instead explains how to consume the returned `name` field, which is the only semantic detail that matters here.

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 gives a specific verb and resource ("List the portal's topic groups") and adds what comes back ("their dataset counts"), which distinguishes it from houston_list_organizations and the dataset-level siblings. An agent knows exactly what this tool produces without opening the schema.

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?

It gives concrete downstream guidance: use a group's `name` as the `group` filter in houston_search_datasets, which tells the agent where this tool fits in a workflow. It stops short of stating when this tool should be avoided or how it relates to houston_list_organizations, so no explicit exclusion is present.

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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