A
licenseA
qualityA
maintenanceEnables fetching any web page's HTML by bypassing anti-bot protection, and also provides AI-parsed structured data and Google search results.
10
4
297
1
MIT
scrapeunblocker-mcp-remote
Server Details
Fetch any web page's HTML, AI-parsed JSON, or Google results via the ScrapeUnblocker anti-bot API
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- ScrapeUnblocker/scrapeunblocker-mcp-remote
- GitHub Stars
- 0
- Server Listing
- ScrapeUnblocker Remote MCP Server
Available Tools
4 toolsfetch_htmlFetch page HTMLARead-onlyInspect
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.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The absolute URL to fetch (http/https). | |
| steps | No | Ordered 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_value | No | The selector/expression paired with wait_method. | |
| wait_method | No | Optional render-wait: 'css' selector or 'js' expression. | |
| proxy_country | No | Optional ISO country code to route through, e.g. 'US'. | |
| sleep_seconds | No | Extra 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.
fetch_parsedFetch AI-parsed page dataARead-onlyInspect
Fetch a web page through the ScrapeUnblocker API (https://developers.scrapeunblocker.com) and return AI-parsed structured JSON instead of raw HTML (product details, article content, listings).
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The absolute URL to fetch and parse. | |
| proxy_country | No | Optional ISO country code, e.g. 'US'. |
TDQS
A4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true. Description adds that it uses the ScrapeUnblocker API and returns AI-parsed JSON with examples, but does not disclose rate limits, authentication needs, or potential failure modes. With annotations covering safety profile, the description adds moderate context beyond 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?
Single sentence is concise, front-loaded with the core action and output format, and every part earns its place with no redundancy or fluff.
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 has two parameters, no output schema, and annotations providing safety context, the description adequately covers its purpose and output type with examples. It does not explain error handling or output shape detail, but this is acceptable for the complexity level.
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?
Both parameters have descriptions in the input schema (url and proxy_country) with 100% coverage. The tool description does not add any additional meaning or context to the parameters beyond what the schema already provides.
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?
Description clearly states the verb 'fetch' and resource 'web page', specifies output as 'AI-parsed structured JSON' with examples (product details, article content, listings), and distinguishes from sibling 'fetch_html' which returns raw HTML.
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?
Description indicates when to use this tool (when you want structured data instead of raw HTML) but does not explicitly state when not to use or directly compare to alternatives like 'fetch_html' or 'google_search'. Context is clear but exclusions are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
google_searchGoogle search resultsARead-onlyInspect
Run a Google search through the ScrapeUnblocker API (https://developers.scrapeunblocker.com) and return organic results as JSON.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | The search query. | |
| proxy_country | No | Optional ISO country code to search from, e.g. 'US'. | |
| pages_to_check | No | How many result pages to collect (default 1). |
TDQS
A3.5/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description does not need to emphasize that it is a read operation. However, it adds value by specifying the external API and that results are limited to organic results in JSON format. It does not disclose potential rate limits, costs, or behavior when results are limited.
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 a single, well-structured sentence that efficiently conveys the tool's purpose and output format without extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three parameters, no output schema, and no nested objects, the description is minimally complete. It covers the core function but lacks detail on the JSON structure or any potential differences in returned data. It is adequate but not rich.
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 coverage is 100%, meaning all parameters are described in the input schema. The description adds no additional meaning beyond what the schema provides. The baseline is 3.
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 that the tool runs a Google search via a specific API and returns organic results as JSON. It uses a precise verb ('Run a Google search') and identifies the resource and output format, distinguishing it from sibling tools like fetch_html and fetch_parsed which retrieve web pages directly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention criteria for choosing google_search over fetch_html or fetch_parsed, nor does it specify any prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_elementsList interactive page elementsARead-onlyInspect
Fetch a page through the ScrapeUnblocker API (https://developers.scrapeunblocker.com) and return its interactive elements (buttons, inputs, selects, links, forms), each with a ready-to-use selector, as JSON {url, count, elements:[...]} instead of raw HTML. Use it to discover what to target, then drive the page with the steps param of fetch_html.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The absolute URL to load and inspect (http/https). | |
| wait_value | No | The selector/expression paired with wait_method. | |
| wait_method | No | Optional render-wait: 'css' selector or 'js' expression. | |
| proxy_country | No | Optional ISO country code to route through, e.g. 'US'. | |
| sleep_seconds | No | Extra seconds to wait after load before inspecting. |
TDQS
A4.3/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds value beyond annotations by specifying the exact JSON return shape, the fact that it fetches through ScrapeUnblocker, and that it returns selectors instead of raw HTML.
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?
Two sentences carry the essential behavior, output format, and usage guidance with no filler. The most important information is front-loaded, and the link to the API docs is placed unobtrusively.
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?
Given the five parameters are fully documented in the schema and the description explains the return contract ({url, count, elements:[...]}), an agent has everything needed to select and invoke the tool correctly. The guidance to follow up with fetch_html also closes the main usage loop.
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 100%, so each parameter is already documented fully. The description adds no parameter-specific semantics beyond the overall purpose, making the schema the primary source. A score of 3 is appropriate for this baseline 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 states a specific verb ('Fetch') and resource ('interactive page elements'), then narrows the output to buttons, inputs, selects, links, and forms with ready-to-use selectors. It also contrasts itself with raw HTML, clearly separating it from fetch_html at a glance.
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 explicitly says when to use this tool: 'discover what to target' before driving the page via fetch_html's `steps` param. It does not spell out when to prefer fetch_parsed or google_search, but the primary routing guidance is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
- Changed
fetch_html1 field changed- added
Input schema / properties / stepsAdded value: +{ + "description": "Ordered 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.", + "items": { + "additionalProperties": false, + "properties": { + "action": { + "description": "The action to perform.", + "enum": [ + "wait_for", + "wait_for_text", + "wait", + "click", + "type", + "select", + "press_key", + "scroll" + ], + "type": "string" + }, + "clear": { + "description": "For 'type': clear the field first.", + "type": "boolean" + }, + "selector": { + "description": "CSS selector the action targets (required for wait_for/click/type/select).", + "type": "string" + }, + "selector_type": { + "description": "How to interpret `selector` (default 'css').", + "enum": [ + "css", + "xPath", + "className", + "tagName" + ], + "type": "string" + }, + "timeout_ms": { + "description": "Per-step timeout override in ms.", + "exclusiveMinimum": 0, + "type": "integer" + }, + "value": { + "description": "Action payload: text to type/select, text for wait_for_text, a key name for press_key (e.g. 'Enter'), milliseconds for wait, or 'bottom'/pixels for scroll.", + "type": [ + "string", + "number" + ] + } + }, + "required": [ + "action" + ], + "type": "object" + }, + "type": "array" +}
- Added
list_elements
3 tool updates
- First observed
fetch_html - First observed
fetch_parsed - First observed
google_search
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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.