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JSON to CSV

json-to-csv

Convert JSON arrays of objects to CSV format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonYesJSON array of objects to convert to CSV
delimiterNoCSV delimiter,
includeHeaderNoInclude header row

Schema Changelog

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

  1. Added

TDQS

A3.5/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden. It states the basic operation but fails to disclose important behavioral traits such as how nested objects are handled, what happens if the input is not an array, or whether the output is a string/file. This is a significant gap for a tool that could encounter varied inputs.

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 one short sentence that immediately communicates the tool's purpose. Every word earns its place, and there is no fluff or repetition. It is a model of conciseness.

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

Completeness3/5

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

The tool is simple (3 params, no output schema), and the description covers the main purpose. However, it does not explain the return value format, error behavior, or edge cases like nested objects. Given the lack of an output schema, this leaves a minor gap but is acceptable for a straightforward converter.

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 schema already documents all parameters (json, delimiter, includeHeader). The description adds minor value by specifying 'arrays of objects', which clarifies the expected input structure, but it does not go beyond this. Baseline 3 is appropriate given full schema coverage.

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 clearly states a specific verb ('Convert') and resource ('JSON arrays of objects' to 'CSV format'), which unambiguously distinguishes it from sibling conversion tools like json-to-typescript or csv-excel-converter. It leaves no doubt about the tool's core function.

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

Usage Guidelines3/5

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

The description implies usage: when you have JSON arrays of objects and need CSV output. However, it does not explicitly mention when to prefer this tool over alternatives (e.g., csv-excel-converter or csv-query), nor any exclusions. The guidance is clear but not explicit.

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

B3.1/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.

Naming Consistency4/5

Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.

Tool Count1/5

202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.

Completeness4/5

The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.

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