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scraperapi-mcp-server

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crawler_job_start

Start an asynchronous crawl from a URL, following links matching a regex to scrape multiple pages. Returns a job ID for tracking progress via polling or webhook.

Instructions

Start a ScraperAPI crawl job from a starting URL.

    Submits an asynchronous crawl that follows links matching a regex outward
    from start_url and scrapes each page. Returns immediately with a job id and
    status (e.g. {"status": "initiated", "jobId": "..."}); the crawl runs in the
    background. Poll 'crawler_job_status' with the returned job id to track
    progress, and/or provide a callback_url webhook to receive results.

    When to use:
    - Crawling multiple linked pages of a site (not a single known URL)
    - Building a dataset by following links to a depth or credit budget

    When NOT to use:
    - Fetching one known URL (use the 'scrape' tool)
    - A structured marketplace/SERP lookup (use the relevant SDE tool)

    Args:
        params (CrawlerJobStartParams): start_url and url_regexp_include are
            required; provide either max_depth or crawl_budget to bound the
            crawl. Optional: url_regexp_exclude, api_params, callback_url,
            additional_data, schedule, enabled.

    Returns:
        str: JSON with the job id and initial status.

    Raises:
        ToolError: If the API key is missing, the rate limit is exceeded, the
            inputs are invalid, or the request fails.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description adds substantial behavioral context beyond annotations: asynchronous execution, immediate return with job id, background crawl, progress tracking methods, bounds via max_depth or crawl_budget, and error conditions (ToolError). No contradictions with 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?

Well-organized with paragraphs, bullet points, and clear sections. Every sentence adds value without redundancy.

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?

The description covers all necessary aspects: purpose, async behavior, tracking, parameters, error handling, and return format. With an output schema existing, the description doesn't need to detail return values further.

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?

While the schema has detailed descriptions for parameters, the tool description provides high-level guidance on required and optional parameters (e.g., start_url and url_regexp_include required, bounds alternatives).

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 starts a ScraperAPI crawl job from a starting URL, explaining it submits an asynchronous crawl that follows links matching a regex. It distinguishes from siblings like 'scrape' and SDE tools.

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

Usage Guidelines5/5

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

Explicit 'When to use' and 'When NOT to use' sections are provided, naming alternative tools ('scrape' for single URLs, SDE tools for structured lookups) and explaining how to track progress via polling or webhook.

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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