ToolForte

JSON Formatter

format_json

Read-onlyIdempotent

Validate and pretty-print JSON with a real parser. Returns formatted JSON or the exact parse error.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`json`	Yes	The JSON text to validate and format
`indent`	No	Spaces per indentation level, 0 to 8 (default 2)

Output Schema

TableJSON Schema

Name	Required	Description
`valid`	No	Whether the input passed every check
`output`	No	The final output of the workflow
`result`	No	The result, when it is not an object

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed3 schema fields changedSep 5, 2026

addedInput schema / properties / indent / description

Added value: +"Spaces per indentation level, 0 to 8 (default 2)"

addedInput schema / properties / json / description

Added value: +"The JSON text to validate and format"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "output": {
+      "description": "The final output of the workflow",
+      "type": "string"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "valid": {
+      "description": "Whether the input passed every check",
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds value by specifying behavior beyond those: validation with 'a real parser' and the return shape ('formatted JSON or the exact parse error'). This gives the agent useful expectations about both success and failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences that front-load the core purpose and then state the return behavior. There is no redundant information, and every sentence contributes meaningful guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, side-effect-free formatting tool, the description, combined with annotations and output schema, is complete. It covers purpose, behavior, success and error output, and the annotations handle safety and idempotency concerns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already fully documents both parameters. The description does not add parameter-level detail beyond the schema, which meets the baseline for high coverage but adds no extra semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Validate and pretty-print JSON with a real parser.' It is further differentiated by mentioning 'Returns formatted JSON or the exact parse error,' which clearly distinguishes it from generic or approximate formatters.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use the tool: whenever JSON needs validation or pretty-printing. It does not explicitly name alternatives or exclusions, and no sibling tool competes directly with this function, but the usage context is still clear enough for an agent to select it appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0

Disambiguation4/5

Most tools target a clearly distinct resource and action, so an agent can usually tell them apart. A few close pairs exist (generate_test_bsn vs generate_brp_test_data, html_to_pdf vs url_to_pdf, read_page vs url_screenshot), but the descriptions draw clear boundaries.

Naming Consistency4/5

Tool names consistently use snake_case and mostly follow a verb_noun pattern like generate_slug, validate_email, or pdf_merge. There are a few noun-style exceptions such as base64, csv_to_json, and password_strength, but no mixed casing or chaotic naming.

Tool Count3/5

40 tools is heavy and exceeds the comfortable selection range for most agents. The server presents itself as a general-purpose utility toolbox, so the breadth is defensible, but the large flat tool list creates real navigation burden.

Completeness4/5

The toolkit covers common encoding, conversion, image/PDF, validation, Dutch-specific test data, memory, and workflow needs quite well. Minor gaps like PDF text extraction or JSON-to-CSV conversion exist, but agents can typically work around them.

Resources

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