Check whether a body is valid JSON. The body is discarded.
| 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 full responsibility for disclosing behavior. It states the body is discarded after the check, which hints at no side effects, but does not explicitly confirm read-only behavior, potential errors, or any other side effects. The description is too sparse to fully inform the agent.
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 that directly states the action. It is efficiently structured with no fluff, though it omits important context about the additional parameters.
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 tool has multiple parameters and no output schema, the description is incomplete. It does not explain how the parameters interact, what the return value looks like, or any error conditions. This leaves significant gaps for an agent trying to use the tool correctly.
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?
All four parameters have descriptions in the schema, but the tool description does not explain how url, host, and zone relate to JSON validation. The json parameter is clearly described as the JSON text to validate, but the others appear arbitrary. This partial clarity earns a middle score.
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 checks whether a body is valid JSON, which is a specific verb and resource. It is distinct from sibling tools like normalize-url or timezone, which serve different purposes. However, the inclusion of url, host, and zone parameters is not explained, creating some ambiguity about the full scope.
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 any competing tools or conditions for selection, leaving the agent to infer applicability solely from the name and description.
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 (URL inspection, time, status codes, JSON validation), but citation and normalize-url both deal with URL parts and could cause confusion. compatibility is also somewhat vague, though it appears to classify requests differently.
All tool names use lowercase with hyphens (e.g., domain-shape, utc-time, validate-json), forming a consistent and predictable pattern across the entire set.
11 tools is within a reasonable range, but the server lacks a unified focus—it's a grab bag of utilities. While not excessive, the count feels high for the apparent scope, which is unclear and fragmented.
There is no coherent domain to assess completeness against. The server is labeled 'Language es' but only one tool (lang-es) relates to language, leaving many potential gaps. For a general utility server, it's missing obvious pairs like URL fetching or timezone listing beyond common names.