Skip to main content
Glama
elephant-xyz

Elephant MCP Server

by elephant-xyz

Get Oracle open-data dataset info

getOracleDatasetInfo

Returns county-level dataset metadata: property counts, per-source coverage, and load timestamps to validate completeness and distinguish missing tables from zero-property counties.

Instructions

Returns dataset-level metadata for a county: county, propertyCount (the catalog-bound appraisal row count when canonical coverage is available, otherwise a live query-table count), state, and provenance/CID fields on the legacy path. When per-source coverage is configured, also returns datasets[] with, per source (appraisal, permits, sunbiz, bbb), ingestedCount, expectedCount, completionPercent, and first/last loaded timestamps — so callers can qualify partial answers by coverage. For a coverage-only county (no property dataset served) propertyCount is null and propertyDatasetAvailable is false, so callers can distinguish a missing property table from a county with zero properties.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countyNoCounty to report dataset info for (case-insensitive). Selects which county's open data to read when the deployment serves multiple counties.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.12.1

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations to lean on, the description carries full behavioral burden and does so thoroughly. It reveals that propertyCount can be either a catalog-bound count or a live query-table count, that provenance/CID fields appear only on the legacy path, that per-source coverage is conditional, and that coverage-only counties return propertyCount null with propertyDatasetAvailable false. This lets callers interpret partial results correctly.

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 front-loaded with the core purpose and then proceeds from common return fields to conditional expansions to the special coverage-only case. Every sentence carries distinct information, and there is no filler or restatement of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema and annotations, the description is remarkably complete: it names the return fields, explains the two computation paths for propertyCount, details the per-source datasets array, and explicitly covers the null-property count edge case. An agent could confidently interpret the response without additional context.

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?

There is only one parameter, county, and the schema already describes it including case-insensitivity, so schema coverage is effectively 100%. The description reinforces that output is per-county but does not add new semantic detail about the parameter itself; baseline 3 is appropriate.

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 states a specific verb and resource: 'Returns dataset-level metadata for a county.' It enumerates the returned fields and conditional variants, making it clearly distinct from sibling tools that retrieve individual properties, schemas, permits, or query plans.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies it is the tool for county-level dataset metadata and explains conditional behaviors, but it never explicitly says when to use this tool instead of a sibling like getOracleProperty or getPropertySchema. No alternatives or exclusions are named, so usage guidance is only implied.

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