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web-fetch-mcp

web-fetch-mcp

by KylinMountain
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

extract_web

Use natural language prompts to extract targeted information from web content across up to 20 URLs.

Instructions

Extract specific information from web content based on natural language prompts

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": {
      "prompt": "<prompt>"
    },
    "name": "extract_web"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesNatural language prompt containing URLs (up to 20) and extraction instructions

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.9/5.0
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 of behavioral disclosure. It indicates the tool uses natural language prompts, but does not mention any limitations, side effects, or operational constraints. The description is merely a functional statement with no transparency beyond that.

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 a single, front-loaded sentence with no redundant information. It is efficient and appropriately sized for a tool with one parameter, though it could have been slightly more informative without losing conciseness.

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?

There is no output schema, so the description should clarify what the tool returns, but it does not. No sibling tool context is provided, and no usage examples or limitations are mentioned. For a tool with minimal annotations and no output schema, the description is incomplete.

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?

The input schema fully documents the single 'prompt' parameter with a clear description (including URLs and extraction instructions), so schema coverage is 100%. The tool description itself adds no additional meaning beyond what the schema already provides, making the baseline of 3 appropriate.

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 clearly states the verb 'Extract' and resource 'web content', indicating a specific extraction action. It distinguishes from sibling tools by the nature of the operation (extract vs summarize/compare), though it does not explicitly name alternatives.

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 is provided on when to use this tool versus alternatives like summarize_web or compare_web. The description only states what it does, without any contextual cues for usage decisions.

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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