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suprsonic-mcp

by O-mega-Enterprise
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TypeScript
Remote

documents

Extract structured data from URLs or raw content by defining an extraction prompt or JSON schema, turning web pages and text into usable fields.

Instructions

Extract structured data from URLs or content. Cost: 3 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL to scrape and extract from.
schemaNoJSON schema for extraction.
contentNoPre-scraped text content.
extraction_promptYesWhat to extract (required unless schema is provided).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.3.1
    • changedInput schema / properties / content / description
      Previous value: -"Pre-scraped text to extract from"New value: +"Pre-scraped text content."
    • changedInput schema / properties / extraction_prompt / description
      Previous value: -"What to extract, in plain language"New value: +"What to extract (required unless schema is provided)."
    • addedInput schema / properties / schema
      Added value: +{
+  "additionalProperties": {},
+  "description": "JSON schema for extraction.",
+  "type": "object"
+}
    • changedInput schema / properties / url / description
      Previous value: -"URL to scrape and extract from"New value: +"URL to scrape and extract from."
    • addedInput schema / required
      Added value: +[
+  "extraction_prompt"
+]
  2. First observedv0.3.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the credit cost (3 credits), a genuine behavioral trait, and 'extract' implies a read-only operation. But it omits return format, error behavior, rate limits, and auth requirements.

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?

Two short sentences, front-loaded with the core action followed by the cost. Every sentence earns its place and there is no filler. It is tersely efficient, arguably at the edge of being under-specified for the tool's complexity.

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

Completeness2/5

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

With no output schema and no annotations, the description should explain the return shape and when each input mode (url vs. pre-scraped content vs. schema-driven extraction) applies. It does neither, and also fails to differentiate this tool from scrape or research, leaving significant gaps for a 4-parameter tool.

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 four parameters, making 3 the baseline. The description adds only marginal value by referencing 'URLs or content', mapping loosely to the url and content params, without clarifying the interplay between url, content, extraction_prompt, and schema.

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

Purpose4/5

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

The description gives a clear verb+resource: 'Extract structured data from URLs or content.' This rescues the vague tool name 'documents'. However, it does not differentiate from siblings like scrape, site-intel, or research, which an agent must distinguish by other means.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance. The phrasing implies it is for structured extraction, and the cost note hints at a tradeoff, but no alternative tool is named (scrape vs. research vs. this) so selection among siblings is left entirely to inference.

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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