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mcp-server-scraper

mcp-server-scraper

by ofershap
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

scrape_url

Extract clean text content from web URLs to retrieve article titles, excerpts, and main content for analysis or processing.

Instructions

Extract clean, readable text content from a URL using Mozilla Readability. Returns title, excerpt, and main content. Best for articles, docs, and blog posts.

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": "scrape_url"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesThe URL to scrape

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
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 extraction method ('using Mozilla Readability') and return format, but lacks details on error handling, rate limits, authentication needs, or performance characteristics. It adequately describes the core behavior but misses deeper operational context.

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

Conciseness5/5

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

The description is front-loaded with the core purpose, followed by return values and usage context in just two sentences. Every sentence adds value without redundancy, making it highly efficient and well-structured for quick understanding.

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

Completeness4/5

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

Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is fairly complete: it covers purpose, method, returns, and usage context. However, it could improve by addressing potential limitations (e.g., handling non-article pages) or output structure details, slightly reducing completeness.

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 has 100% description coverage, with the 'url' parameter fully documented in the schema itself. The description doesn't add any parameter-specific details beyond what the schema provides, such as URL format constraints or examples. This meets the baseline for high schema coverage.

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 tool's purpose with specific verbs ('Extract clean, readable text content') and resources ('from a URL using Mozilla Readability'), distinguishing it from siblings like extract_links (which extracts links) and extract_metadata (which extracts metadata). It also specifies the return values (title, excerpt, main content) and ideal use cases (articles, docs, blog posts).

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

Usage Guidelines4/5

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

The description provides clear context on when to use this tool ('Best for articles, docs, and blog posts'), which helps differentiate it from siblings like scrape_multiple (for multiple URLs) or search_page (which might involve searching). However, it doesn't explicitly state when NOT to use it or name specific alternatives, keeping it from a perfect score.

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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