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?
The description discloses that the body is discarded, which is a behavioral detail. However, it does not explain what 'body' refers to, nor does it clarify the roles of the url, host, and timezone parameters, which appear unrelated to JSON validation. This lack of explanation reduces transparency about how the tool actually processes its inputs.
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, consisting of two short sentences. It conveys the purpose and a key side effect without any unnecessary words or filler, making it highly efficient.
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 missing essential context about the tool's inputs. The presence of unrelated parameters (url, host, timezone) alongside 'json' creates confusion about what the tool actually does. The description does not explain why these parameters exist or how they relate to validating a JSON body, leaving significant gaps in understanding.
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 adds no explanation for any parameters. The schema itself provides descriptions for each field, and the json parameter's schema description aligns with the tool's purpose. Since schema coverage is 100%, the baseline is 3, and the description neither enriches nor detracts from the parameter meanings.
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 purpose: 'Check whether a body is valid JSON.' It uses a specific verb ('Check') and specifies the resource ('body'), making the core function unambiguous. The name 'validate-json' exactly matches the description.
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 gives no guidance on when to use this tool versus alternatives. It does not mention any conditions, prerequisites, or contexts in which validation is appropriate. The sibling tools like normalize-url and timezone are not referenced, leaving the user to infer the tool's applicability.
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 clearly distinct outputs: URL metadata, URL normalization, hostname labels, robots inspection, HTTP status catalog, time lookups, JSON validation, and hex encoding. The main ambiguity is between citation and normalize-url, which both return host/scheme information, and between timezone and utc-time, though the descriptions help clarify their different outputs.
All names use lowercase hyphenation, giving a surface-level consistency. However, the set mixes nouns like citation and timezone, verb-object forms like inspect-robots and normalize-url, and the unusual hex-ok, so there is no consistent naming pattern.
With 11 tools, the count is reasonable and within the well-scoped range. The tools span URL, time, and data utility categories without feeling redundant, though the breadth suggests a general-purpose utility server rather than a tightly focused one.
The set covers common URL, time, and simple data-validation needs, but the overall domain is broad and somewhat unclear. Obvious companion operations are missing, such as hex decoding, timezone conversion, or more detailed request inspection beyond the vague compatibility tool.