Return origin, host, and path for a URL. Query and fragment are dropped.
| 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 provided, the description fully carries the behavioral burden and explicitly discloses that query and fragment are dropped—a non-obvious behavioral trait. It also defines the output components (origin, host, path). It does not mention edge cases such as invalid URLs or handling of missing inputs, but the core transformation is transparent.
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 focused sentence that front-loads the primary function and immediately discloses the key transformation. Every word earns its place; there is no repetition or filler.
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?
With no output schema, the description appropriately explains the return values (origin, host, path) and the components that are dropped. It does not cover error behavior, the fact that all parameters are optional, or the roles of the non-URL parameters, but for a simple transformation tool this is a minor gap.
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 descriptions cover 100% of parameters, so the baseline is 3. The description adds no parameter-level meaning and does not clarify why 'host', 'json', and 'zone' are inputs to a URL normalization tool. The schema descriptions themselves are present but seem mismatched with the tool purpose, and the description does not resolve this confusion.
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 specific action ('Return origin, host, and path') and resource ('a URL'), clearly distinguishing it from URL validation or other operations. It also specifies that query and fragment are dropped, which further clarifies the behavior.
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?
No guidance is given on when to use this tool versus alternatives, and no exclusions or related tools are mentioned. The description only states what the tool does, leaving the agent to infer appropriate usage context.
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.
Several tools have overlapping concerns: citation, normalize-url, and domain-shape all analyze URLs/hostnames, while timezone, utc-time, and iana-zones all relate to time. The purpose of compatibility is vague and could be confused with the URL inspection tools. Only a few tools like slug-ok and validate-json are clearly distinct.
All names use lowercase hyphenation, which is consistent, but the pattern is mixed: some are verb phrases (normalize-url, inspect-robots, validate-json), while others are bare nouns (citation, compatibility, timezone). There is no unified verb_noun convention, though the names remain readable.
Eleven tools is not an unreasonable count by itself, but the tool set is unfocused for a server named 'Slug character check.' Most tools address unrelated concerns such as time, URLs, HTTP status, and JSON, making the collection feel padded rather than purpose-built.
The server lacks a coherent domain: slug checking has only one thin tool, URL utilities have no encoding/decoding or query-param handling, and time utilities lack conversions or formatting options. For any single stated purpose, the surface has significant gaps and no end-to-end workflow.