security_emailLive DNS check of a domain's email authentication records. $0.01 per call.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain to check, without scheme (e.g. example.com) | |
| selector | No | Optional DKIM selector to look up (e.g. google, default, s1) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive behavior. The description adds that this is a live DNS check and that it costs money per call, which are useful behavioral details beyond the annotations. It does not contradict the annotation's safety profile.
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 concise sentence plus a cost note. Every word earns its place, and the core purpose is front-loaded.
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?
With only two parameters, one required, and rich read-only annotations, this definition is adequate for an agent to call correctly. There is no output schema, and the description does not spell out the return format, but the title and purpose make the expected DNS-record results inferable.
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%, and the schema already documents both 'domain' and 'selector' clearly. The description adds context about DNS records but does not add meaningfully beyond the schema's parameter definitions.
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 uses a specific verb and resource: 'Live DNS check of a domain's email authentication records,' and the title clarifies the scope to SPF/DMARC/DKIM. This makes it easy to distinguish from security_tls and security_typosquat without opening schemas.
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 implies usage for checking email authentication/spoofing posture, which is clear context, but it does not explicitly say when to prefer this over sibling tools or when not to use it. There is no misleading guidance, just no explicit alternatives.
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.
Most tools are cleanly separated by domain prefix (data_, security_, validate_, verify_) and describe distinct outputs. A couple of pairs like token_verdict vs verify_token or data_portfolio vs wallet_dossier could be confused until descriptions are read, but the descriptions resolve the ambiguity.
The majority of tools follow a predictable prefix_subject pattern, e.g. data_block, security_tls, validate_iban, verify_payment. A few outliers like html_to_markdown, text_diff, wallet_dossier, and token_verdict use different conventions, but the overall system remains readable.
20 tools is on the heavy side for the typical MCP server and sits in the 16–25 'feels heavy' zone. Most tools have a legitimate purpose, but the five validate_* identifier tools plus two generic utilities could feel like surface area bloat.
The server covers a broad and coherent read/validation domain: chain data, token safety, payments, security checks, and identifier validators. Minor gaps exist, such as lack of detailed historical transaction/activity data and no general network/domain security scan beyond email, TLS, and typosquat.