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ip2whois

mcp-ip2whois

Official
by ip2whois
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Python
Remote

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.2.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one resolves IP addresses to hosted domains, the other retrieves WHOIS data for domain names. There is no functional overlap.

    Naming Consistency5/5

    Both tools follow the consistent verb_noun pattern (get_hosted_domains, get_whois), making the naming predictable and easy to understand.

    Tool Count3/5

    With only two tools, the server feels minimal for the domain of IP and domain information. While the tools cover core functionalities, the count is at the lower boundary of what's reasonable.

    Completeness3/5

    The tools cover hosted domains and WHOIS lookups, but common related operations like IP geolocation, domain availability checks, or reverse IP lookups are missing. The surface is functional but not comprehensive.

  • Average 4.2/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are present, so description carries full burden. It discloses that the tool returns a JSON string with domains and total count, but does not mention any limitations, rate limits, error handling, or data source freshness. For a simple lookup, this is adequate but not highly transparent.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is short and includes structured Args/Returns sections. It is clear and to the point, though the Returns section could be more concise.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple tool with one parameter and no nested objects, the description covers the essential behavior. The presence of an output schema (even if not detailed here) reduces the need to explain return values further.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 0%, but the description adds clear meaning to the single required parameter 'ip', specifying it expects an IPv4 or IPv6 address. This significantly helps an agent understand what to provide.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states it is a lookup for hosted domain names by IP address. The verb 'Lookup' and resource 'hosted domain names' are specific, and it distinguishes from sibling tool 'get_whois' which does WHOIS lookups.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage context (reverse DNS lookups) but does not explicitly state when to use this tool versus alternatives. No exclusions or when-not-to-use guidance is provided.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries full burden. It describes the return format and fields, indicating it is a read-only lookup, but does not mention error handling or authorization needs.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is concise with an effective structure: purpose statement, Args, Returns. Every sentence adds value with no waste.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool is simple with one parameter and an output schema, the description covers parameter and return data well. It lacks mention of errors or limitations, but is otherwise complete.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The domain parameter is clearly described with purpose and an example. Schema has no description (0% coverage), so the description fully compensates by explaining what the parameter is.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states it performs a WHOIS lookup for a domain name, listing specific details like registrar, expiry, nameservers, etc. It is distinct from the sibling tool get_hosted_domains by focusing on registration data.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly says when to use this tool: when user asks about domain registration details, registrar, expiry, etc. However, it does not mention when not to use or differentiate from the sibling tool.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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