run
Fast email validation at the edge: syntax, MX records, disposable-domain detection.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
Fast email validation at the edge: syntax, MX records, disposable-domain detection.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With empty annotations, the description carries the full burden of behavioral disclosure. It lists what the tool checks but does not mention return format, error behavior, synchronous/asynchronous execution, or side effects, and there is no output schema to fill that gap.
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?
A single compact sentence that front-loads the core purpose and lists the concrete validation checks. There is no filler, repetition, or unnecessary detail.
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?
The description explains what the tool does but leaves the input contract and output behavior entirely unspecified. With no annotations and no output schema, an agent would struggle to construct a correct request or interpret the result.
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 0%, and the description does not explain how to fill the required 'input' field. The schema shows an object with arbitrary string property names and arbitrary values, which is meaningless without additional explanation, and the description provides none.
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 identifies the tool as an email validator and enumerates specific checks: syntax, MX records, and disposable-domain detection. This is a clear function statement, though there are no sibling tools to differentiate from, so it stops short of a 5.
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?
No guidance is given on when to use this tool versus alternatives, what prerequisites exist, or what kind of input payload is expected. The 'at the edge' phrasing hints at a lightweight use case but does not provide actionable selection guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Only one tool exists, so there is zero ambiguity about which tool to use. The tool's description clearly states its purpose (email validation), leaving no room for confusion.
The tool name 'run' is a generic, vague verb that gives no indication of email validation. While consistency is trivially satisfied with a single tool, the name itself is uninformative and fails to follow a descriptive noun-verb pattern.
With only one tool, the server feels thin for a typical MCP surface, but it is focused on a single validation task. The scope is narrow enough that one tool might be acceptable, yet it borders on being too minimal for a comprehensive utility.
The single tool covers all standard email validation checks: syntax, MX records, and disposable-domain detection. This is a complete lifecycle for basic validation, though more advanced features (e.g., deliverability checks) could be a minor gap.