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epa_facility_search

Read-onlyIdempotent

Search EPA-regulated facilities by state, city, zip, and/or facility name. Returns each facility's Registry ID (needed for the other EPA tools), address, and a snapshot of its compliance status across Clean Air Act, Clean Water Act, RCRA (waste), and Safe Drinking Water programs. Provide at least one filter; broad queries (e.g. state only for a large state) may be rejected as too broad, so add a city, zip, or name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNo5-digit ZIP code (e.g. '20010').
cityNoCity name (e.g. 'Washington').
nameNoFacility name or fragment (e.g. 'Pepco', 'refinery').
limitNoMaximum facilities to return (default 25, max 100).
stateNoTwo-letter state or territory code (e.g. 'DC', 'TX', 'CA').
active_onlyNoIf true, only return facilities flagged with active enforcement/compliance activity.

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the read-only, idempotent, non-destructive safety profile. The description adds genuine behavioral context beyond annotations: broad queries may be rejected, at least one filter is required, and the return payload covers Registry ID, address, and a multi-program compliance snapshot. No contradiction with the readOnlyHint.

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?

Three sentences, each earning its place: the core action, the return value with downstream relevance, and the filter/query-construction constraint. Everything is front-loaded with no filler or 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?

With no output schema, the description appropriately carries the return-value burden by listing Registry ID, address, and the compliance programs covered. It also discloses rejection behavior and the filter requirement. Slightly shy of a 5 only because it omits minor details like result ordering or the behavior of name-fragment matching.

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 coverage is 100%, so each of the six parameters is already documented in the input schema. The description adds a cross-parameter constraint not captured in the schema (at least one of state/city/zip/name must be provided) and warns against overly broad combinations, which is useful but modest on top of the schema's heavy lifting.

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?

States a specific verb ('Search') and resource ('EPA-regulated facilities'), enumerates the filter dimensions, and details the return payload. The mention that Registry ID is 'needed for the other EPA tools' positions this as the entry point to the EPA tool family, distinguishing it from detail/compliance-oriented siblings like epa_facility_details.

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?

Gives concrete, actionable usage conditions: 'Provide at least one filter' and warns that broad queries like state-only for a large state 'may be rejected as too broad.' This is clear context for constructing valid calls. However, it never names sibling alternatives or explicit when-not-to-use conditions (e.g., 'use epa_facility_details once you have a Registry ID'), so it stops short of a 5.

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.