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 behavioral burden. It discloses that the body is discarded, which is useful, but it does not explain what the tool returns, how errors are handled, or that only the 'json' property is relevant and other schema properties appear unrelated.
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 brief and front-loaded, with two short sentences that state purpose and the key side effect. It is efficiently sized, though it omits important clarification about 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?
The description is too sparse to correctly call the tool given the mismatched schema, no output schema, and no usage guidance. It fails to clarify which parameters are actually used and what response shape to expect.
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?
Although schema coverage is 100%, the schema descriptions for url, host, and zone are clearly irrelevant to a JSON validation tool. The description does not clarify that these are extraneous or that only 'json' should be populated, so the agent is likely to be misled about the expected inputs.
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 verb and resource: it checks whether a body is valid JSON and explicitly notes the body is discarded. It is clear on the core purpose, though it does not differentiate from sibling tools or specify the exact output format.
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 provided on when to use this tool versus alternatives, nor are any preconditions or exclusion criteria mentioned. The description only says what the tool does, leaving the agent to infer 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.
Most tools have distinct purposes, but timezone/utc-time both return current time and citation/normalize-url both inspect URL components. Compatibility is vague and could be confused with status-catalog, though descriptions provide some help.
All tool names use lowercase-hyphenated style, but they mix noun labels (citation, timezone, status-catalog) with verb-object actions (inspect-robots, normalize-url, validate-json). This mixed semantic pattern makes naming less predictable despite the consistent formatting.
Eleven tools is not inherently too many, but a server titled 'Leap year check' carries only one leap-year tool among unrelated URL, time, HTTP, and JSON utilities. This is a major scope mismatch for the stated purpose.
The set lacks a coherent domain, so completeness is hard to assess: for a leap-year server there is only the bare check, and as a general utility server there are obvious omissions like date arithmetic or more detailed HTTP capabilities. Agents would hit dead ends beyond the narrow included functions.