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Glama

LiveDataLink

parcel_search

Read-onlyIdempotent

Search property parcels by street address and get assessed value, land use, and most recent sale for each match. Coverage: Maryland statewide (all 24 jurisdictions, includes sale prices) and Harris County, TX / Houston (appraised value only, no sale prices since Texas is a non-disclosure state). Returns valuation and characteristics only, not owner names. Use parcel_details for the full record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows (default 10, max 50).
queryYesStreet address fragment, e.g. '100 Main St' or 'Charles St'.
stateNo2-letter state code. Coverage: 'MD' (Maryland statewide) or 'TX' (Harris County / Houston only). Defaults to MD.
countyNoOptional county name to narrow results, e.g. 'Baltimore', 'Montgomery'.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The annotations already signal a safe read-only, idempotent operation, so the bar is lower, but the description still adds meaningful behavior: coverage boundaries, the Texas non-disclosure impact on sale prices, the exclusion of owner names, and the fact that results include only valuation and characteristics. This exceeds what the schema or annotations imply.

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 compact and front-loaded: the core action and return fields appear first, followed by coverage caveats and a pointer to the sibling tool. Every sentence earns its place, with no filler or redundant restatement of the tool name.

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 no-output-schema search tool, the description covers the important return content, jurisdictional limitations, and the alternative for fuller data. It does not describe pagination behavior or default ordering, but those are partially documented in the limit parameter and are not critical for correct invocation.

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 the baseline is 3, and the description adds value by framing query as a 'street address fragment' and explaining the MD/TX state coverage and county narrowing behavior. It does not need to repeat the schema's per-parameter descriptions because those are already complete.

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 action ('Search property parcels by street address'), a clear object (parcels), and the exact fields returned ('assessed value, land use, and most recent sale'). It also distinguishes itself from parcel_details by directing users there for the full record, and it disambiguates from owner-name tools by stating owner names are not returned.

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 gives concrete usage context: statewide Maryland coverage with sale prices, Harris County/TX with appraised value only, and no owner names. It explicitly names parcel_details as the alternative for the full record. It does not mention other related siblings like parcel_coverage or parcel_sales_history, so some routing guidance is left 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.