List MX records (exchange + priority, sorted) for a domain via free DNS-over-HTTPS to gauge mail deliverability. Accepts a bare domain or a full email address. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| No | Email address (its domain is used if domain is omitted) | ||
| domain | No | Domain name (bare host) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description takes responsibility for behavioral disclosure. It explicitly states 'Read-only; price 0.0 (free)' and describes the output format ('exchange + priority, sorted'). This clearly communicates safety and cost, though it doesn't cover failure modes like missing MX records.
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?
Two sentences, front-loaded with the primary action and output, followed by input handling and cost. Every sentence earns its place.
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?
Although there is no output schema, the description specifies the return content (exchange + priority, sorted) and the method (DNS-over-HTTPS). For a low-complexity read-only tool with two optional parameters, this is sufficient. Minor gap: no explanation of behavior for invalid domains or absent MX records.
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 coverage is 100% with both 'email' and 'domain' described. The description adds that either a bare domain or a full email address is accepted, which aligns with the schema's note that the email's domain is used if domain is omitted. No additional semantic detail is provided beyond the schema.
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 opens with a specific verb and resource: 'List MX records (exchange + priority, sorted)' for a domain. This clearly distinguishes it from sibling tools like email_verify_check_spf or domain_intel_dns_lookup by focusing specifically on MX records and mail deliverability.
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?
It states the purpose ('to gauge mail deliverability') and the accepted input types ('bare domain or a full email address'). This gives clear context for when to use the tool, though it doesn't explicitly name exclusions or alternative tools.
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 have clearly distinct purposes, especially the ledger-watch groups with domain prefixes. However, there are near-duplicate utilities such as content_authenticity_domain_reputation and domain_intel_reputation, and fx_tax_convert overlaps with price_oracle_fx_rate/convert. The sheer number of tools also increases the chance of selecting the wrong one, though descriptions are generally clear.
The naming is largely consistent with a <domain>_<action> or <domain>_<watch>_<action> pattern, and all names use snake_case. Minor deviations include standalone names like entity_search, kyb_report, verify_receipt, and the confusing singular/plural pair of sanction_watch_* and sanctions_screen_*. Overall, the pattern is predictable.
With 172 tools, this server is far beyond the typical well-scoped range. It bundles dozens of unrelated utility domains (weather, carbon, CVE, geo, etc.) alongside the Japan public-ledger watches, making it unwieldy for an agent to navigate. This extreme count is a major coherence problem.
For the core Japan public-ledger domain, coverage is excellent: each ledger has search, get, timeline, recent_changes, and verify_ledger, plus cross-ledger entity_search and temporal_query. The unrelated utility areas are also fairly complete for their own purposes, but the server's scope is so broad that some utilities are duplicated (e.g., multiple currency converters). Overall, no critical dead ends in the main domain.