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creatorpiyush

mcp-web-agent

Scrape a webpage

web_scrape

Fetch any URL and return clean content as markdown or structured JSON via CSS selectors. Uses a lightweight HTTP request first, then a browser only when JavaScript rendering is required.

Instructions

Fetch a URL and return clean content — markdown by default, or specific fields via a CSS-selector schema. Tries a plain HTTP fetch first and only launches a browser if the page needs JS to render.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
formatNomarkdown
schemaNofield name -> CSS selector, required when format=json
selectorNoscope markdown extraction to this CSS selector subtree
forceBrowserNoskip the static-fetch tier for pages known to require JS
ignoreRobotsNoignore robots.txt restriction rules
Behavior4/5

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 explains the output format (markdown vs. schema fields) and the smart fetch strategy ('Tries a plain HTTP fetch first and only launches a browser if the page needs JS to render'). It does not mention robots.txt enforcement or timeout behavior, but the core behavior is well disclosed.

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 two sentences, front-loaded with the main action ('Fetch a URL and return clean content'), and every clause adds meaningful behavior. No fluff or redundancy; it is an exemplary concise description.

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?

For a tool with 6 parameters, no output schema, and no annotations, the description covers the essential context: primary use, output formats, and the JS-rendering fallback. It omits details like default robots.txt behavior and error handling, but it is sufficiently complete for an experienced agent to invoke the tool correctly in most scraping scenarios.

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 67%, so the description should add some semantic value. It does clarify the 'format' parameter by saying 'markdown by default' and introduces the 'CSS-selector schema' concept. However, it does not describe 'selector', 'forceBrowser', or 'ignoreRobots', though those do have schema descriptions. Overall, it adds moderate value beyond the 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 clearly states the tool's function: 'Fetch a URL and return clean content', with a specific output mode (markdown or CSS-selector schema). It distinguishes itself from siblings by focusing on single-page scraping, but it does not explicitly name alternative tools like web_crawl_get_page, so it falls just short of a 5.

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?

The description implies when to use this tool (for fetching and cleaning a webpage's content), but it offers no explicit comparison to alternatives, no exclusions (e.g., when to use web_crawl instead), and no mention of prerequisites or limitations. The usage context is clear but not fully elaborated.

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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