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 the behavioral burden. It usefully discloses that the body is discarded, implying a non-persistent validation operation. However, it does not state the return value, invalid-JSON behavior, or whether other schema fields affect the operation.
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?
Two short, front-loaded sentences with no filler. The key behavioral fact that the body is discarded is included efficiently, and every sentence earns its place.
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 there is no output schema and no annotations, the description is incomplete: it omits the result format, error handling, and how the unrelated optional parameters should be treated. An agent cannot fully predict tool behavior or confidently construct a correct call.
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 description coverage is 100%, but most parameter descriptions are irrelevant to JSON validation and appear copied from sibling tools (url, host, zone). The description does not map 'body' to the json parameter or clarify that only 'json' should be used, making parameter selection confusing.
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 ('check') and a specific target ('body' valid JSON), and adds that the body is discarded. It is not a tautology and is clearly about validating JSON, though it does not explicitly differentiate from siblings. The use of 'body' rather than 'json' introduces minor ambiguity.
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 about when to use this tool versus alternatives, nor are any exclusions or prerequisites mentioned. The only implied context comes from the tool's name and generic action, so an agent must infer usage.
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 overlap: citation and normalize-url both return URL origin/host information, while timezone and utc-time both provide current time. The descriptions help separate most tools, but compatibility is vague and could be confused with classification or request-checking tools.
Names use lowercase hyphenation and are generally readable, but they mix verb-led forms like inspect-robots, normalize-url, and validate-json with noun-led forms like domain-shape, status-catalog, and utc-time. There is no consistent verb_noun or noun_verb convention across the set.
11 tools is a reasonable count, but for a server named 'Nano ID shape check' the scope feels diffuse, with URL, time, JSON, and HTTP status utilities included. Several tools do not clearly earn their place under that stated purpose.
The server claims a narrow Nano ID focus, yet only one tool directly supports it, while URL, JSON, time, and robots checks are shallow one-offs. There are no tools for generating or custom-validating Nano IDs, and URL handling stops at normalization without redirects or deeper request inspection.