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LiveDataLink

parcel_details

Read-onlyIdempotent

Get the full record for one parcel by its account id: address, current assessed value (total, land, improvement), land use, zoning, year built, structure square footage, lot size, coordinates, and most recent sale. Valuation and characteristics only, no owner name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNo2-letter state code. Coverage: 'MD' (Maryland statewide) or 'TX' (Harris County / Houston only). Defaults to MD.
account_idYesParcel account id (from parcel_search).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

The annotations already mark this as readOnly and idempotent, so the safety profile is clear. The description adds meaningful behavioral scope by listing exactly what data is included and explicitly excluding owner name. Minor gaps remain, such as not mentioning whether fields can be null or whether recent sales may be absent, but these are not critical given the readOnly annotation.

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 a single focused sentence that front-loads the core action and then lists the returned fields in a compact, scannable way. Every phrase adds value, and the 'no owner name' clarification is a useful boundary statement with no redundancy.

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?

For a simple read-only lookup tool with no output schema, the description is quite complete: it names the input, the source of the input, the full set of returned characteristics, and the notable exclusion. It could be slightly stronger by mentioning what happens when data is unavailable or by pointing explicitly to parcel_sales_history for more sale detail, but these are not required for basic correct usage.

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 description coverage is 100%, so the input schema already documents both parameters, including state coverage and the fact that account_id comes from parcel_search. The description reinforces that account_id is the lookup key but adds no additional parameter detail beyond the schema. This meets the baseline for fully covered schemas.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get'), the resource ('full record for one parcel'), and the key identifier ('account id'), and it enumerates the specific fields returned. It is easy to distinguish from sibling tools like parcel_search and parcel_sales_history in practice, though it does not explicitly name an alternative. The phrase 'Valuation and characteristics only, no owner name' helps set precise expectations.

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 implies this tool is used after obtaining an account_id, and the schema notes the id comes from parcel_search. However, it does not explicitly state when to prefer this over siblings such as parcel_sales_history or parcel_search, nor does it list exclusion criteria beyond 'no owner name.' Usage context is present but mostly implicit.

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

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.