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mcp-server

mcp-server

by atamayop2018
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

extract_scraped_info

Retrieve scraped website information by provider name, URL, or domain for comparing LLM inference pricing.

Instructions

Extract information about a scraped website.

Args: identifier: The provider name, full URL, or domain to look for

Returns: Formatted JSON string with the scraped information

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "identifier": "<identifier>"
    },
    "name": "extract_scraped_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
identifierYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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 only says 'extract' and that it returns a JSON string, but does not disclose whether this is a read-only operation, what happens if the identifier is not found, or any rate limits or error conditions. Minimal disclosure of behavior beyond the basic action.

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 very short and to the point, with the main purpose front-loaded. No redundant phrasing or filler. It is concise without being under-specified.

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?

For a simple one-parameter tool with an output schema, the description is minimal. It lacks context about the relationship with scrape_websites, any prerequisites, or potential failure modes. The output schema covers the return format, but the description does not tell the agent enough about when or why to use this tool.

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

Parameters4/5

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

Schema coverage is 0%, but the description compensates by explaining that 'identifier' can be a provider name, full URL, or domain. This adds meaningful semantics beyond the schema's bare 'Identifier' label, though it could be more specific about accepted formats.

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?

States a clear verb (extract) and resource (scraped website), and the sibling scrape_websites is clearly different (scraping vs extracting). It does not specify what 'information' includes, but the purpose is unambiguous.

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?

No guidance on when to use this tool versus the sibling scrape_websites. The description does not mention prerequisites (e.g., that the website must have been scraped first) or any conditions that would make this tool the right choice.

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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