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Documentation Index

Fetch the complete documentation index at: https://docs.linkup.so/llms.txt

Use this file to discover all available pages before exploring further.

This page is structured for direct use as integration context for a coding agent, or as a function-calling tool definition. Operational guidance is repeated inline so the page is self-contained.

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Linkup /fetch integration guide

You are integrating the Linkup /fetch API: a real-time page content extractor. Given a URL, it returns clean LLM-ready markdown. Optional JavaScript rendering is available for client-side-rendered pages, along with optional raw HTML and image URL extraction. Limits: pages up to 20 MB, HTML only. Latency: ~1s.

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When to use it

Use /fetch when the URL is already known: typically after /search has narrowed the candidates, or when a user has supplied the URL directly. Other endpoints in the API:
  • Search (/search): when no URL is available and web content must be located.
  • Research (/research): autonomous research agent. Async, 2–20 minutes depending on depth.
  • Tasks (/tasks): asynchronous batch wrapper around Search, Fetch, and Research.

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Setup

pip install linkup-sdk            # Python
# or
npm install linkup-sdk            # TypeScript

export LINKUP_API_KEY="your-api-key"

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Example (Python; adapt to the project’s language)

from linkup import LinkupClient

client = LinkupClient(api_key="<YOUR_LINKUP_API_KEY>")

# renderJs: true is the safer default for unknown sites.
# Many modern marketing sites and SPAs require it.
response = client.fetch(
    url="https://docs.linkup.so",
    render_js=True,
)
print(response)

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Tool definition (OpenAI function-calling format)

Remove the "type": "function" envelope and rename parameters to input_schema for the Anthropic format. 
{
  "type": "function",
  "function": {
    "name": "linkup_fetch",
    "description": "Fetches a URL and returns clean LLM-ready markdown. Handles JavaScript-rendered pages when renderJs is true. HTML pages only, up to 20 MB. Use whenever the URL is already known.",
    "parameters": {
      "type": "object",
      "properties": {
        "url": {
          "type": "string",
          "description": "The URL to fetch. Must be a valid HTTP/HTTPS URL pointing to an HTML page (not a binary file)."
        },
        "renderJs": {
          "type": "boolean",
          "description": "Render the page's JavaScript before extraction. Default false. For agentic pipelines, set to true by default to ensure the full page content is extracted; many modern sites require it. Set to false only after the specific site has been confirmed to render server-side.",
          "default": false
        },
        "includeRawHtml": {
          "type": "boolean",
          "description": "Return the raw HTML alongside the markdown. Default false. Set to true for workflows that need full page HTML, or when complex structure (tables, custom elements) is erased during markdown conversion.",
          "default": false
        },
        "extractImages": {
          "type": "boolean",
          "description": "Extract image URLs alongside the markdown. Default false. Set to true for workflows that consume images (product photos, charts, recipe images).",
          "default": false
        }
      },
      "required": ["url"]
    }
  }
}

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Operational guidance (inline)

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renderJs selection

For agentic pipelines, set renderJs to true by default to ensure the full content of each page is extracted. A page that requires JavaScript rendering and does not receive it returns near-empty markdown. The cost is 0.001withoutrenderingand0.001 without rendering and 0.005 with rendering. Set renderJs to false only when all the URLs to be accessed have been confirmed to render server-side.

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When to use Fetch

Fetch is purpose-built to extract the content of a webpage that has been identified. Linkup’s Fetch can be used as a stronger alternative to typical fetch tools because it can render JavaScript.

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The Search → Fetch pattern

search = client.search(
    query="Datadog pricing tiers",
    depth="standard",
    output_type="searchResults",
)

for r in search.results[:3]:
    page = client.fetch(url=r.url, render_js=True)
    # feed page.markdown to your LLM, or extract fields directly
Use Search to find candidate URLs and Fetch to retrieve them in full when the agent needs to reason over the full page content rather than the snippets returned by Search.

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Constraints

  • Fetch returns a 400 error for binary file URLs (PDFs, ZIPs).
  • Fetch returns a 400 error for pages over 20 MB.
  • Fetch does not authenticate. It returns the response a logged-out visitor would see.
  • Setting extractImages to true adds latency; enable it for workflows that consume image URLs.
  • includeRawHtml should be true only when the raw HTML is required.

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TypeScript notes

  • Import: import { LinkupClient } from 'linkup-sdk'.
  • Method: await client.fetch({ url, renderJs }). Single object argument.
  • Field names are camelCase: renderJs, includeRawHtml, extractImages.