domain_infoWHOIS/RDAP dossier for a domain: registrar, creation/expiry, status, nameservers. ~$0.005.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain name, e.g. example.com |
| Name | Required | Description | Default |
|---|---|---|---|
| result | No |
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 include readOnlyHint: false, destructiveHint: false, and openWorldHint: true. The description adds cost (~$0.005) and the protocol (WHOIS/RDAP), which goes beyond the annotations. It does not contradict the annotations; readOnlyHint false isn't contradicted because the description never claims to be read-only. The cost disclosure is useful behavioral information.
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 entire description is a single sentence that front-loads the core purpose ('WHOIS/RDAP dossier') and lists key data points concisely. Cost information is included at the end. There is no wasted words or repetition.
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 tool with an output schema and annotations, the description covers the essential purpose, outputs (registrar, dates, status, nameservers), and cost. It is sufficiently complete for an AI agent to decide whether to invoke it and what to expect. The simplicity of the tool doesn't require additional context.
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% and the only parameter 'domain' has a clear description in the schema ('Domain name, e.g. example.com'). The tool description doesn't add additional parameter details, so it meets the baseline but doesn't exceed it.
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 provides a WHOIS/RDAP dossier for a domain, listing specific data points (registrar, creation/expiry, status, nameservers). This distinguishes it from sibling tools like web_search or scrape_page, which handle different kinds of lookups.
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 when to use the tool: when you need domain registration details. It does not mention alternatives or exclusions, but the specific scope (WHOIS/RDAP) makes the usage context clear. Since it's a single-purpose tool among less similar siblings, this is adequate.
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 (image, music, video, vision, voice, etc.), but some overlap exists: ask_ai vs ask_ai_pro differ only in model strength, and web_search vs research_report both involve search with AI responses. Descriptions help clarify, though an agent could misselect in edge cases.
Tool names follow a mostly consistent snake_case pattern, with many using an 'ai_' prefix for generation tasks. However, name styles vary between verb_noun (call_endpoint, remove_bg) and noun_verb (crypto_prices, domain_info), and ask_ai/ask_ai_pro break the ai_ prefix convention. Minor deviations, but the overall pattern is readable.
At 16 tools, the server is slightly above the ideal 3-15 range but remains well-scoped for a multi-purpose utility server. Each tool has a distinct function, and the count feels manageable rather than overwhelming.
The server covers a broad set of capabilities (AI generation, web search, crypto, domain info), but it lacks lifecycle management for generated assets—there are no list/get/delete operations for previously created media, and the domain appears to be a collection of paid endpoints rather than a cohesive service.