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scrapedatshi

scrapedatshi-mcp

Official
by scrapedatshi

crawl_site

Crawl an entire website and return structured JSON chunks from all pages. Choose between sitemap mode for docs/blogs or spider mode for any site by following links.

Instructions

Crawl an entire website, chunk all pages, and return structured JSON chunks. Two modes: 'sitemap' (reads sitemap.xml — best for docs/blogs) and 'spider' (follows links — works on any site).

Use this when the user wants chunks from MULTIPLE pages WITHOUT extracting structured fields. For structured field extraction across pages, use extract_crawl.

⚠️ ALWAYS confirm the max_pages limit with the user before calling. Default is 10 pages. For large sites, warn about credit usage first.

If contextual_retrieval is requested, follow the PRE-FLIGHT sequence:

  1. Call verify_provider_key(provider, 'llm') → get live model list

  2. Ask user to choose a model

  3. Ask about JS rendering

  4. Present Contextual Retrieval as a recommended upgrade

LLM keys can be omitted if set as environment variables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe root domain or sitemap URL to crawl.
selectorNoOptional CSS selector applied to every crawled page.
js_renderNoUse headless browser to render JS before scraping each page. Ask the user before enabling. Adds surcharge per page.
llm_modelNoLLM model name from verify_provider_key. Do not guess or hardcode.
max_pagesNoMaximum pages to crawl. Default: 10. Maximum: 200. Always confirm with user for large sites.
crawl_modeNo'sitemap': reads sitemap.xml (best for docs/blogs). 'spider': follows links from root URL (works on any site).sitemap
llm_api_keyNoAPI key for the LLM provider. Can be omitted if set as env var.
llm_providerNoLLM provider for contextual retrieval. Verify with verify_provider_key first.
exclude_patternNoSkip URLs containing this substring (e.g. '/blog/').
include_patternNoOnly crawl URLs containing this substring (e.g. '/docs/').
contextual_retrievalNoEnable RAG 2.0 contextual enrichment. Present as a recommended upgrade. Requires llm_provider and llm_model from verify_provider_key.
Behavior4/5

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

With no annotations provided, the description carries full responsibility for disclosing behavior. It explains the crawling and chunking process, two modes, and confirms that it returns structured JSON. However, it does not detail the exact structure of the return JSON (e.g., field names), which is a gap in transparency. The warnings about confirmation and credit usage add valuable behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-structured with a front-loaded summary, followed by distinct sections for mode differentiation, warnings, and a pre-flight sequence. It is longer than necessary but each sentence serves a purpose, and the organization helps the agent parse key information quickly. A slight reduction in length could improve conciseness without losing clarity.

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's complexity (11 parameters, 1 required, no output schema), the description covers usage, modes, warnings, and a complex workflow (contextual retrieval pre-flight). However, it does not describe the output format or error handling, which are important for a complete understanding. The absence of an output schema means the agent must infer the return structure, leaving a minor gap.

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 the baseline is 3. The description adds little beyond the schema: it reiterates the two modes and the max_pages default but does not provide new insights for parameters like 'selector', 'exclude_pattern', or 'include_pattern'. The schema already has adequate descriptions, so the description offers marginal additional value.

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 crawls an entire website, chunks pages, and returns structured JSON. It specifies two modes ('sitemap' and 'spider') and distinguishes itself from the sibling tool 'extract_crawl' by noting that this tool is for obtaining chunks from multiple pages without structured field extraction.

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?

The description provides explicit when-to-use and when-not-to-use guidance: use for multiple pages without structured fields, use 'extract_crawl' for structured extraction. It also includes practical warnings (confirm max_pages, warn about credit usage) and a pre-flight sequence for contextual retrieval, making it easy for the agent to decide and invoke correctly.

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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