Parse and analyze a URL. Returns protocol, hostname, port, path, query parameters, fragment, and validation status.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL to analyze (e.g. https://example.com/path?query=1) |
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. It does state that the tool returns URL components and a validation status, making it clear this is a parse-and-report operation. However, it does not disclose how invalid URLs are handled (return status vs. error), whether any network access occurs, or the exact nature of the validation status, leaving some behavioral ambiguity.
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 well-structured sentence that front-loads the action and then lists concrete outputs. There is no filler, no repetition, and no unnecessary verbiage; every element contributes to understanding what the tool does.
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 one parameter, no annotations, and no output schema, the description is largely complete: it identifies the resource and enumerates all output categories an agent would need to know about. The main gap is that it does not specify the data type or format of the validation status, which could matter when interpreting results.
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 already provides 100% coverage for the single url parameter, including type, required flag, and a concrete example. The description restates that a URL is parsed but adds no parameter-specific detail beyond what the schema supplies, which meets the baseline of 3 for full schema coverage.
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 begins with a specific verb phrase, 'Parse and analyze a URL,' and explicitly names the resource and the returned components: protocol, hostname, port, path, query parameters, fragment, and validation status. This clearly differentiates it from sibling tools, which all operate on different data types such as base64, cron, CSV, JSON, JWT, Markdown, regex, semver, and UUID.
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 implies the use case—when you need to break a URL into its components or validate it—but provides no explicit when-to-use or when-not-to-use guidance, nor does it reference any alternatives. The sibling tools are distinct enough that the right choice is fairly obvious, so the absence is not severe, but the guidance is only implicit.
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 distinct operation—encoding, color conversion, parsing, hashing, JWT validation, Markdown rendering, regex testing, SemVer operations, diffing, URL analysis, and UUID generation. The four SemVer tools are related but cleanly separated by action (bump vs compare vs max vs satisfies), and descriptions clarify their boundaries.
Tools overwhelmingly follow an object_verb snake_case convention (base64_encode, csv_parse, regex_test, semver_bump). Semver_max and semver_satisfies deviate slightly from the imperative verb pattern, but the overall naming is predictable and searchable.
At 16 tools, the server is slightly above the ideal 3–15 tool range but each utility earns its place for a general-purpose developer toolbox. No tools feel redundant, and the count remains manageable because the names and domains are highly scannable.
The toolkit covers a solid breadth of common developer utilities: encodings, common formats (JSON, CSV, Markdown), hashing/JWT, regex, SemVer, cron, URL, UUIDs, and diffing. It lacks some fringe converters such as YAML/XML parsing or HTML escape/unescape, but these are minor gaps that agents can work around rather than dead ends.