xml_to_json
Convert XML document to JSON (attributes as @attr). When: Convert XML → JSON for agents that prefer JSON tools.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Convert XML document to JSON (attributes as @attr). When: Convert XML → JSON for agents that prefer JSON tools.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
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?
No annotations are provided. The description mentions a specific behavior (attributes as @attr) but does not disclose other important traits such as input validation, error handling, or handling of namespaces, CDATA, or comments. For a straightforward conversion tool, this is adequate but lacks detail.
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 exceptionally concise with two sentences. The first sentence clearly states the core functionality, and the second adds a usage guideline. No unnecessary words or fluff. Well-structured and front-loaded.
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?
Considering the tool has only one parameter, no output schema, and no annotations, the description covers the essential purpose and usage context. It does not detail output format, error conditions, or limitations, but for a simple conversion tool this is fairly complete. The sibling tools also support the context.
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 has one parameter 'text' with 0% description coverage. The description does not add any additional meaning or constraints to the parameter beyond the schema. Since coverage is low, the description should compensate but fails to do so, leaving the parameter's expected format and semantics ambiguous.
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 'Convert XML document to JSON (attributes as @attr).' It specifies the action (convert), the source format (XML), target format (JSON), and a key detail about attribute handling. This distinguishes it well from sibling conversion tools like csv_to_json, yaml_to_json, etc.
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 includes a 'When: Convert XML → JSON for agents that prefer JSON tools.' This provides clear guidance on when to use the tool, but does not explicitly mention when not to use it or provide alternatives. The context is sufficient but could be more comprehensive.
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.
Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.
All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.
193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.
Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.