MailboxValidator Email Validation MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't reveal any behavioral traits such as rate limits, authentication requirements, error handling, or what constitutes a 'free email' (e.g., based on domain lists). The mention of 'using MailboxValidator' hints at an external service but doesn't clarify implications like API dependencies or costs.

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 a single, efficient sentence that front-loads the core purpose without unnecessary details. It uses clear language and avoids redundancy, making it appropriately sized for a simple tool with one parameter.

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 simplicity (1 parameter, no output schema, no annotations), the description is minimal but incomplete. It lacks context on behavioral aspects like how results are returned (e.g., boolean vs. detailed report), error scenarios, or integration with MailboxValidator. For a tool that likely involves external API calls, more completeness is needed to guide 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?

The input schema has 100% description coverage, with the parameter 'emailAddress' clearly documented. The description adds no additional meaning beyond the schema, as it doesn't explain parameter constraints, examples, or edge cases. With high schema coverage, the baseline is 3, and the description doesn't compensate with extra insights.

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: 'Checks if an email address is a free email using MailboxValidator.' It specifies the verb ('checks'), resource ('email address'), and the specific type of check ('free email'). However, it doesn't explicitly differentiate from sibling tools like 'check_disposable_email' or 'validate_email', which likely perform different types of email validation.

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 no guidance on when to use this tool versus its siblings. It doesn't mention alternatives like 'check_disposable_email' or 'validate_email', nor does it specify contexts where checking for free emails is appropriate (e.g., for security filtering vs. marketing). Usage is implied by the purpose but lacks explicit when/when-not instructions.

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