EPA Air Quality System (AQS) MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions authentication details ('Email and API key can be provided or will use AQS_EMAIL/AQS_API_KEY environment variables'), which is valuable context. However, it doesn't describe the return format (e.g., what data fields are included), pagination behavior, rate limits, or error conditions. For a read operation with 9 parameters and no annotations, this leaves significant gaps in understanding how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized. It starts with the core purpose, provides a usage note, details parameters with examples, includes a geographic example, and ends with authentication info. Most sentences earn their place, though the parameter section is lengthy (but necessary given the complexity). It could be slightly more front-loaded by moving the authentication note earlier, but overall it's efficient and clear.

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

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

Given the tool's complexity (9 parameters, no annotations, no output schema), the description is adequate but has clear gaps. It covers authentication and parameter semantics well, but lacks details on the return format (what data the monitors include), pagination, rate limits, or error handling. For a tool that likely returns structured data, the absence of output schema means the description should do more to explain what to expect, leaving the agent with incomplete context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds substantial value beyond the schema: it provides common AQS parameter codes with pollutant names (e.g., '44201: Ozone'), clarifies date format constraints ('must be same calendar year'), gives examples of bounding box values, and includes a real-world example for Los Angeles. This compensates well for the schema's technical descriptions, though it doesn't cover all 9 parameters equally (e.g., email/key are only briefly mentioned).

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

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

The description clearly states the tool's purpose: 'Get all air quality monitors within a latitude/longitude bounding box.' It specifies the verb ('Get'), resource ('air quality monitors'), and geographic scope ('bounding box'), distinguishing it from sibling tools like aqs_monitors_by_cbsa or aqs_monitors_by_county that use different geographic units. The phrase 'Useful for querying monitors in a geographic region that may span multiple states or counties' further clarifies its unique use case.

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

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

The description provides clear context for when to use this tool: 'Useful for querying monitors in a geographic region that may span multiple states or counties.' This implicitly suggests it's for cross-boundary queries, but it doesn't explicitly state when not to use it or name specific alternatives among the many sibling tools (e.g., aqs_monitors_by_state for single-state queries). The guidance is helpful but lacks explicit exclusions or named comparisons.

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