Skip to main content
Glama

scrapeunblocker-mcp-remote

Fetch page HTML

fetch_html
Read-only

Fetch the fully rendered HTML of any web page through the ScrapeUnblocker API (https://developers.scrapeunblocker.com), bypassing anti-bot protection (Cloudflare, DataDome, PerimeterX, Akamai, Shape). Use when a normal fetch is blocked (403/429, captcha) or the page needs a real browser. Returns raw HTML. Pass steps to interact with the page (search, click, paginate) before capture - use the list_elements tool first to discover selectors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe absolute URL to fetch (http/https).
stepsNoOrdered browser actions to run in a real browser after the page loads (wait_for, wait_for_text, wait, click, type [human-like], select, press_key, scroll), then return the resulting HTML. NON-IDEMPOTENT: it runs once and is not retried. A failed step returns a 422 naming the offending step plus the page HTML at that point. Discover selectors with list_elements first.
wait_valueNoThe selector/expression paired with wait_method.
wait_methodNoOptional render-wait: 'css' selector or 'js' expression.
proxy_countryNoOptional ISO country code to route through, e.g. 'US'.
sleep_secondsNoExtra seconds to wait after load.

TDQS

A4.7/5.0
Behavior5/5

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

Even with annotations already declaring readOnlyHint and openWorldHint, the description adds meaningful behavioral detail: it routes through ScrapeUnblocker, bypasses anti-bot systems (Cloudflare, DataDome, PerimeterX, Akamai, Shape), requires a real browser, and returns raw rendered HTML. The step-based interaction model is also disclosed, and nothing in the description contradicts the annotations.

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 compact and front-loaded: purpose, use condition, return type, and step guidance are covered in a few dense sentences before the schema takes over. Every sentence adds information rather than repeating the schema or annotations.

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

Completeness5/5

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

For a tool with one required parameter and no output schema, the description tells the agent what is returned (raw HTML), when to use the tool, and how to prepare interactions. The schema covers remaining parameter details and failure behavior (422 with step name and HTML), so nothing critical is missing for correct invocation.

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

Parameters4/5

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 practical value for the main nontrivial parameter, `steps`, by explaining its purpose ('search, click, paginate') and directing the agent to use list_elements first for selector discovery. Other parameters like proxy_country and sleep_seconds remain schema-only, which is acceptable at full 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 opens with 'Fetch the fully rendered HTML of any web page', naming a specific verb, resource, and output. It also distinguishes itself from sibling fetch_parsed by emphasizing 'fully rendered' and 'raw HTML', and from google_search by targeting arbitrary pages rather than search results.

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?

It explicitly states when to use the tool: 'Use when a normal fetch is blocked (403/429, captcha) or the page needs a real browser.' It also advises using list_elements first to discover selectors. However, it does not explicitly name fetch_parsed as the alternative for when parsed content is preferred, though 'Returns raw HTML' implies that choice.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.2/5.0
Disambiguation5/5

Each tool maps to a distinct output type: rendered HTML, parsed JSON, search results, or element selectors. fetch_html and fetch_parsed both fetch a page but explicitly serve different extraction needs, so an agent can reliably tell them apart.

Naming Consistency4/5

All names use lowercase snake_case and mostly follow an action_target pattern: fetch_html, fetch_parsed, list_elements. google_search breaks the pattern slightly but is still predictable and readable.

Tool Count5/5

Four tools is a compact but well-scoped set for a scraping API wrapper. Each tool exposes a distinct capability and none is redundant.

Completeness5/5

The set covers the core scraping lifecycle: rendering HTML, getting structured data, searching Google, and discovering selectors for interaction. Combined with the steps parameter on fetch_html, agents can navigate, interact, and extract without major gaps.