Short catalog of common HTTP status codes.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
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?
With no annotations, the description carries the full burden of behavioral disclosure. 'Catalog' implies a read-only reference, but it does not state whether the tool makes any external calls, whether it requires network access, or what it returns. It also does not explain how the parameters affect behavior, leaving side effects and data usage opaque.
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 description is a single, concise sentence, which is appropriately sized for a simple reference tool. However, it is under-specified rather than efficiently packed; it does not include essential context about parameters or usage. It is concise but not structured to maximize usefulness.
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 tool with four parameters, no output schema, and no annotations, the description is critically incomplete. It does not explain the return value, how parameters are consumed, or any behavioral nuances. An agent has no basis for selecting or invoking this tool correctly beyond guessing.
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 has 100% coverage with descriptions for all four parameters, but the tool description adds no explanation of how these parameters relate to the catalog. An agent cannot infer whether the parameters are filters, inputs for normalization, or entirely unused. The description fails to bridge the schema to the tool's purpose.
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 states a clear purpose: a short catalog of common HTTP status codes. It is specific about the resource (status codes) and the action (catalog). It does not explicitly differentiate from siblings, but the sibling tools are clearly about different domains (citation, compatibility, etc.), so the purpose is distinct enough.
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?
There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites, conditions for use, or when not to use it. The description is purely descriptive and offers no decision-support for an agent.
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 distinct purposes, but 'citation' and 'normalize-url' overlap in parsing URLs and returning host/scheme details, while 'compatibility' is vaguely described. Overall, the boundaries are mostly clear.
Names are consistently lowercase and hyphenated, but mix noun-style names ('timezone', 'citation') with verb-style names ('inspect', 'normalize', 'validate'). There is no uniform verb_noun pattern, making the naming style inconsistent.
With 11 tools, the count is reasonable for a utility-focused server and within the typical 3-15 range. Each tool addresses a distinct aspect, though some could be consolidated.
The set covers URL parsing, HTTP status, timezones, robots.txt, language tags, and JSON validation, but lacks broader web-development utilities like DNS lookups or header inspection. The domain is not fully defined, so some gaps are possible.