Return host, scheme, and HTTP status for a URL. Page content is not stored.
| 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?
The description discloses that page content is not stored, which is a transparency statement about data retention. However, it omits other behavioral aspects: it implies making an HTTP request to fetch the status but does not state this, nor does it mention redirects, error handling, network timeouts, or whether authentication is required. Since no annotations are provided, the description carries the full burden but only partially fulfills it.
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 extremely concise, using only two sentences to convey the core purpose and a key behavioral note. It is front-loaded with the primary action and avoids any fluff or redundancy. The structure is logical and easy to parse.
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?
Given the mismatch between the description and the parameter set, the description is incomplete. It does not explain the additional parameters (host, json, zone) or how they relate to the stated function. It also lacks details about output format, error conditions, or whether the tool makes network requests. This incompleteness could lead an agent to misuse the tool or misunderstand its capabilities.
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 description does not explain the role of the parameters. It mentions 'a URL' but does not specify that the 'url' parameter is the input, nor does it clarify the purpose of the 'host', 'json', and 'zone' parameters, which seem unrelated to the stated functionality. While the schema provides individual parameter descriptions, they appear disconnected from the tool's primary purpose, creating confusion rather than adding clarity.
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's function with a specific verb ('Return'), the specific resources (host, scheme, HTTP status), and the input (a URL). It also adds a relevant note that page content is not stored, which clarifies the scope. This distinguishes it from sibling tools like normalize-url or status-catalog.
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 provides no guidance on when to use this tool versus alternatives. It does not mention scenarios or prerequisites. For example, it does not say 'Use this when you need to check a URL's reachability' or compare itself to normalize-url. The lack of usage context leaves the agent uncertain about tool selection.
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 target distinct operations—text counting, JSON validation, robots inspection, time utilities—and descriptions clarify the differences. The main risk is citation versus normalize-url, since both describe URL components, and timezone versus utc-time could occasionally cause misselection.
Names are readable and consistently lowercase, but they mix styles: verb-object names like normalize-url and validate-json, noun compounds like char-count and status-catalog, and single nouns like citation and compatibility. There is no uniform verb_noun pattern.
At 11 tools, the set is well within the ideal range and each utility addresses a separate use case. No obvious redundant or filler tools are present.
The surface covers text validation, URL inspection, robots, time, and HTTP status reasonably well for a privacy-focused utility server. Missing conveniences like timezone conversion or URL encoding are minor and can be worked around.