FetchV2

Discover all links on a webpage. Use this BEFORE fetch_batch to find relevant URLs. USE THIS TOOL WHEN: - Exploring a documentation site to find relevant pages - Building a list of URLs to fetch in batch - Finding all subpages under a section (e.g., all /api/ docs) - Checking what content exists before deciding what to read RECOMMENDED WORKFLOW: 1. discover_links(url="https://docs.example.com/", filter_pattern="/guide/") 2. Review the returned links and select relevant ones 3. fetch_batch(urls=[selected_urls], max_length_per_url=1500) FILTER EXAMPLES: - filter_pattern="/docs/" → Only links containing '/docs/' - filter_pattern="getting-started|quickstart" → Links with either term - filter_pattern="\.md$" → Only markdown file links NOTES: - Returns up to 100 links (more are noted but omitted to save context) - Relative URLs are automatically resolved to absolute URLs - JavaScript/mailto/anchor links are excluded

Fetch a single webpage and extract its main content as clean markdown. USE THIS TOOL WHEN: - You need to read an article, documentation page, or blog post - You want clean, readable text without boilerplate (navbars, ads, footers) - The user provides a specific URL to read DO NOT USE WHEN: - You need to fetch multiple URLs (use fetch_batch instead - fewer round trips) - You want to discover what pages exist on a site (use discover_links first) PAGINATION: Large pages are automatically truncated. The response will include 'use start_index=N to continue' - call again with that value to get more content. EXAMPLES: - fetch(url="https://docs.example.com/guide") → Get documentation page - fetch(url="https://example.com/api", max_length=2000) → Shorter response to save context - fetch(url="https://example.com/data", include_tables=True) → Preserve tabular data

Fetch multiple webpages in a single request and return combined content. USE THIS TOOL WHEN: - You have 2-10 URLs to read (e.g., from discover_links results) - Comparing content across multiple pages - Gathering context from several documentation pages at once KEY BENEFIT: One tool call instead of multiple fetch() calls = fewer round trips, faster results, and reduced overhead in supervised/approval workflows. WORKFLOW EXAMPLE: 1. discover_links(url="https://docs.example.com", filter_pattern="/api/") 2. fetch_batch(urls=[...returned links...], max_length_per_url=1500) NOTES: - Each URL's content is separated by '---' dividers - Failed URLs show inline errors without stopping other fetches - Robots.txt is NOT checked for batch fetches (assumes prior discovery)

Fetch and parse an llms.txt file to discover LLM-friendly documentation. USE THIS TOOL WHEN: - A site provides an llms.txt file for AI-friendly content discovery - You need to understand what documentation is available - You want to fetch structured docs in a single request WHAT IS llms.txt: A proposal for sites to provide LLM-friendly content at /llms.txt. It's a markdown file listing documentation links with descriptions. See https://llmstxt.org for the specification. WORKFLOW: 1. fetch_llms_txt(url="https://example.com/llms.txt") → Get structure 2. Review sections and links 3. Either use include_content=True or fetch_batch for specific pages EXAMPLES: - fetch_llms_txt(url="https://fastht.ml/docs/llms.txt") - fetch_llms_txt(url="https://example.com/llms.txt", include_content=True)