USE THIS to verify an IP address before relying on it — do not assume a dotted or colon string is valid. Strictly checks IPv4 (RFC 791, rejects leading zeros / out-of-range octets) and IPv6 (RFC 4291, including '::' compression and embedded IPv4), and returns the version.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | The IPv4 or IPv6 address to validate. |
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 mark readOnlyHint=true, and the description adds valuable behavioral details: strict RFC 791 compliance for IPv4 (rejecting leading zeros/out-of-range) and RFC 4291 for IPv6 (including compression and embedded IPv4), and that it returns the version. No contradiction with annotations.
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 an imperative usage directive. Every sentence adds critical information without redundancy. Highly efficient.
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?
While the description covers validation logic and return of version, it does not specify the exact return format (e.g., boolean, object). With no output schema, this gap could affect an agent's interpretation of the tool's output.
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 a single parameter described as 'The IPv4 or IPv6 address to validate.' The description enriches this by clarifying the strict validation checks and return value, adding context beyond the schema's basic description.
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 explicitly states the tool validates IP addresses, specifies IPv4/IPv6 with RFC details, and distinguishes from sibling validation tools by focusing on IP format. The verb 'validate' and resource 'IP' are clear and specific.
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 begins with 'USE THIS to verify an IP address before relying on it', providing explicit guidance on when to use it. It does not mention alternatives or when not to use, but the sibling tools are all format-specific validators, making the context clear.
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.
Each tool targets a specific identifier or operation (e.g., validate_iban, parse_date, is_holiday). Even similar tools like validate_isbn and validate_isbn10 are distinct by version. There is no overlap or ambiguity.
Most tools follow a verb_noun pattern (validate_xxx, parse_xxx, format_currency). The exception is 'next_holiday', which uses an adjective instead of a verb. Otherwise consistent.
With 47 tools, the set is very large. While each tool is distinct, the count exceeds the recommended range (25+ is considered too many) and may overwhelm users or agents.
Covers a wide array of international identifiers and utilities, but notable gaps exist (e.g., no Canada SIN, India PAN, Mexico CURP). The set is broad but not exhaustive for the domain of data validation.