Domain intelligence (RDAP) — Registration intelligence for any domain: creation/expiry dates, age in days, registrar, statuses, nameservers. Source: registry RDAP. JSON. Price: $0.005 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | domain name, e.g. example.com |
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds non-obvious context beyond annotations: the data source (registry RDAP), output format (JSON), and the explicit price ($0.005 USDC via x402), which is important for agent decisions. No contradiction.
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 dense sentences plus compact fragments deliver the core purpose, returned fields, source, format, and price with no filler. Information is front-loaded and every clause adds value.
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?
For a single-parameter lookup with no output schema, the description lists the key returned fields and the JSON format, plus cost and source, making selection and invocation straightforward. Annotations cover the safety profile, so nothing essential is missing.
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 already documents the single parameter with an example (domain name, e.g. example.com) and has 100% schema description coverage. The description adds nothing about parameter format, normalization, or edge cases, so the baseline of 3 applies.
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?
Description clearly identifies the tool as returning RDAP-based registration intelligence for a domain, and enumerates concrete fields: creation/expiry dates, age, registrar, statuses, nameservers. This distinguishes it from siblings like domain_brand_protection and domain_due_diligence because it focuses on raw registry registration data.
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?
Provides clear usage context: it's for registration data for any domain via RDAP, and the listed fields imply the intended scenario. However, it does not explicitly name alternatives or state when not to use it, so sibling differentiation is left to inference.
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.
Many tools are clearly separated by prefix and data source, but several bundled products overlap heavily: vehicle_deal_check vs vehicle_report, realestate_property_report vs realestate_site_risk, finance_company_360 vs finance_health_scan, and domain_due_diligence vs email_domain_check/business_vet. An agent would frequently struggle to pick the correct premium bundle.
Tool names overwhelmingly follow a consistent snake_case category-prefix pattern like weather_, crypto_, vehicle_, finance_, and geo_. Minor deviations such as bare names (domain, ip) and noun-verb forms (dns_lookup, url_check) are easy to learn and don't create real confusion.
50 tools is far beyond the typical well-scoped 3–15 range and will require heavy filtering to navigate. The broad multi-domain data marketplace partially justifies the size, but it would be more coherent split into per-domain servers or consolidated further.
For a read-only data/diligence marketplace, the surface is quite comprehensive: weather, vehicle, crypto, SEC/finance, domain/email, sanctions, and geo workflows all have core operations plus fused verdict bundles. Minor gaps exist—such as a simple crypto price lookup or vehicle market value—but agents can usually work around them.