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MWIE MCP Server

MWIE MCP Server

by tmolavi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

extract_page_content

Convert a webpage URL into clean text or structured Markdown, removing navigation, ads, and other web noise.

Instructions

Extract clean text and structured Markdown from a webpage, discarding web noise.

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": {
      "url": "<url>"
    },
    "name": "extract_page_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
render_jsNo
generate_markdownNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden, and it only discloses one behavioral trait: noise removal. It says nothing about permissions, rate limits, failure modes, or what happens when JS rendering is required, which matters for a fetch tool with three options.

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?

A single front-loaded sentence with no filler and no redundancy. It is efficient but so terse that brevity shades into under-specification.

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?

An output schema exists, so return values need not be explained, but that is the only thing covered. With zero annotation coverage and zero parameter documentation, an agent lacks the information to set render_js or generate_markdown correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for all three parameters. It only obliquely touches generate_markdown by advertising Markdown output, and says nothing about url or render_js, whose purpose is not inferable from a bare boolean name.

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 names a specific verb and resource ("Extract clean text and structured Markdown from a webpage") and adds scope in "discarding web noise". It never distinguishes itself from siblings like crawl_url or extract_structured_data, so an agent cannot tell from the text alone why it should pick this over those.

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?

"From a webpage" hints that this is the single-page option versus the crawl_* siblings, but that routing is implied rather than stated. There is no explicit when-to-use, when-not-to-use, or named alternative.

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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