Web Scraping Remote MCP Server

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, destructiveHint=true), the description discloses meaningful behavior: proxy management and geo-targeting, the requirement that blocking features need JS rendering, and billing implications (autoMode is billed and chosen values are returned in requestMetadata). It doesn't elaborate on the destructive/open-world side effects flagged by annotations, but adds real 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.

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

The purpose and when-to-use guidance are front-loaded, and the size is justified by the 21-parameter surface. However, the core content is delivered as one very dense compound sentence, which is information-rich but harder to scan than a structured breakdown would be.

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

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

With no output schema, the description carries the return-value burden and does so well: 'Returns HTML, text, markdown, and/or JSON along with status code, extracted emails and links, CSS-selector extractions, and AI-structured fields per schema.' Combined with the feature enumeration, an agent has everything needed to call this complex tool correctly.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds conceptual framing above the schema by grouping capabilities (jsScenario actions like click/scroll/fill/waitFor, extractRules vs aiExtractRules for LLM extraction) and clarifying that output is HTML/text/markdown/JSON, which helps an agent reason about parameter combinations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb (scrape/fetch) and resource (any public URL via managed proxies) and enumerates the distinct capabilities: JS rendering, custom headers, wait conditions, jsScenario actions, screenshots, blocking, and extractRules/aiExtractRules. No siblings exist, so no differentiation is needed, and an agent can immediately tell this is the universal fetcher.

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

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

It explicitly routes usage: 'Use as a fallback/universal fetcher for sites without a dedicated API, for scraping JS-heavy SPAs, capturing screenshots, or producing clean markdown/structured JSON.' This gives clear when-to-use conditions, though it states no explicit exclusions or named alternatives (none exist among siblings).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.