json format
json_formatValidate and pretty-print JSON (2-space indent). Reports the error location if invalid.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| json | No | ||
| indent | No |
json_formatValidate and pretty-print JSON (2-space indent). Reports the error location if invalid.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| json | No | ||
| indent | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / indentAdded value: +{
+ "type": "number"
+}Input schema / properties / jsonAdded value: +{}Input schema / properties / urlAdded value: +{}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that it validates and pretty-prints, and reports error location on invalid input, which is useful. However, it does not mention whether it modifies input, requires network access, or any side effects. It does not contradict annotations (there are none), and the description is accurate about its core behavior.
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, front-loaded with the purpose and a key detail (error location). It earns its place with no wasted words.
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 tool has 3 parameters with no schema descriptions, no annotations, and no output schema. The description is too sparse to guide the agent on how to provide input (url vs json), what the output structure looks like, or any edge cases. It covers the basic functionality but lacks sufficient detail for effective invocation.
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 0%, and the input schema has three properties (url, json, indent) with no descriptions. The description mentions the indent (2-space) but does not clarify the purpose of 'url' or 'json' parameters, nor how they relate (e.g., one or the other?). The description adds minimal meaning beyond the schema, leaving ambiguity.
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 validates and pretty-prints JSON with a 2-space indent, and reports error location if invalid. This distinguishes it from siblings like diff_text, redact_text, and what_can_you_do, though it does not explicitly differentiate from validate_json or json_yaml, but the pretty-print and error location aspects are specific.
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 implies usage for validating and formatting JSON, but provides no explicit guidance on when to choose this over validate_json or json_yaml. It does not mention when not to use it or alternative tools. The mention of error location could be useful for debugging, but the context is not fully developed.
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 clear, separate purposes: diff, redact, regex, JWT, SQL, timezone, units, QR, screenshot. The main overlap is between json_format and validate_json, since both parse and validate JSON, though their outputs differ enough to be workable.
The majority follow a clear snake_case verb_noun or noun_verb pattern like diff_text, transpile_sql, and timezone_convert. sql_from_description and what_can_you_do break the pattern, but the rest is predictable and readable.
14 tools is well-scoped for a general-purpose developer utility server. Each tool covers a distinct practical need, and the count does not feel bloated for the breadth of features offered.
The toolkit covers a broad range of everyday dev utilities: text diffing, redaction, regex, JSON/YAML, SQL, time, units, JWT, QR, and screenshots. Some common basics like base64, hashing, or URL encoding could be useful additions, but the surface is complete enough for its stated purpose.