Houston Open Data MCP

Describe a Houston table

houston_describe_table

Read-onlyIdempotent

Inspect a queryable Houston Open Data resource's column names, data types, and row count before querying so filters and sorting use real fields.

Instructions

List a queryable resource's columns, types, and total row count.

Call this before houston_query_records so that filters, column lists, and sorting use real column names. Only works when queryable is true.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "resource_id": "<resource_id>"
    },
    "name": "houston_describe_table"
  }
}

Input Schema

Name	Required	Description	Default
`resource_id`	Yes	Resource `id` (UUID) from houston_get_dataset.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 6, 2026

TDQS

A4.4/5.0

Behavior4/5

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 covered. The description adds genuinely new behavioral context the annotations cannot express: the `queryable` precondition that gates whether the call succeeds. It stops short of saying what happens on failure (error vs. empty result), which keeps it from a 5.

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 sentences, no filler. The capability statement comes first and the sequencing advice plus precondition follow, so the agent gets the core fact before the caveats.

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?

The output schema covers the return value, the single parameter is fully documented, and annotations cover safety, so little is left for the description to carry. The only real omission is the failure behavior when `queryable` is false, which an agent would benefit from knowing.

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?

With a single parameter at 100% schema coverage, the schema already explains that resource_id is a UUID obtained from houston_get_dataset. The description adds no further meaning about the identifier, so the baseline of 3 applies.

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 names a specific verb (list) and specific outputs (columns, types, total row count) for a named resource, going well beyond the title's 'Describe a Houston table'. An agent can tell this is a schema-introspection tool rather than a data-retrieval or dataset-lookup tool, distinguishing it from houston_query_records and houston_get_dataset.

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 states an explicit ordered usage: call this before houston_query_records so filters, column lists, and sorting use real column names. It also names a precondition for the tool to work at all ('only works when queryable is true'), which functions as a when-not condition.

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

Deploy Server