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he-yang

Excel to JSON MCP by WTSolutions

by he-yang

Excel to JSON MCP by WTSolutions - from url

excel_to_json_mcp_from_url

Convert Excel files from public URLs to JSON format with configurable output options for structured data extraction.

Instructions

Convert Excel (.xlsx) from publicly accessible URL(string format) to JSON. If you do not have a Pro Code, please pass only the url parameter, but not options parameter in the request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublically accessible URL(string format) to Excel file(.xlsx)
optionsNoIf you do not have a Pro Code, please do not pass the options parameter in the request.
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the Pro Code requirement which suggests authentication/authorization needs, but doesn't address rate limits, error handling, response format, or what happens with invalid URLs. The description adds some behavioral context but leaves significant gaps for a tool that performs data transformation.

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

Conciseness4/5

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

The description is appropriately sized with two sentences that both earn their place. The first sentence states the core purpose, and the second provides crucial usage guidance. However, it could be slightly more front-loaded by mentioning the Pro Code requirement earlier, and the URL format specification is redundant with the schema.

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?

For a data transformation tool with no annotations and no output schema, the description provides adequate purpose and usage guidance but lacks information about output format, error conditions, or transformation behavior. The 100% schema coverage helps, but the description should ideally mention what the JSON output looks like or reference the schema for details.

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?

With 100% schema description coverage, the schema already documents both parameters thoroughly. The description adds minimal value beyond the schema - it reiterates the URL requirement and Pro Code conditional logic, but doesn't provide additional context about parameter interactions or usage patterns. This meets the baseline expectation when schema coverage is complete.

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 the specific action ('Convert Excel from publicly accessible URL to JSON'), identifies the resource type (.xlsx files), and distinguishes from the sibling tool 'excel_to_json_mcp_from_data' by specifying 'from url' in both the title and description. The verb+resource+scope combination is precise and unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use specific parameters: 'If you do not have a Pro Code, please pass only the url parameter, but not options parameter in the request.' This creates clear conditional usage rules and distinguishes between free and pro usage scenarios, offering practical implementation guidance.

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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