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.

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 and PDF only. Latency: ~1s.

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.

Setup

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

export LINKUP_API_KEY="your-api-key"

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)

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. Supports HTML and PDF pages up to 20 MB. Handles JavaScript-rendered HTML pages when renderJs is true. 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 or PDF page."
        },
        "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"]
    }
  }
}

Operational guidance (inline)

`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

0.001 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.

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.

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.

Constraints

Fetch supports HTML and PDF. Other binary URLs (ZIPs, images, videos) return a 400 error.
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.

TypeScript notes

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

Get Started

Endpoints

Platform

Guides

Tutorials

FAQ

Fetch for AI agents

Linkup `/fetch` integration guide

When to use it

Setup

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

Tool definition (OpenAI function-calling format)

Operational guidance (inline)

`renderJs` selection

When to use Fetch

The Search → Fetch pattern

Constraints

TypeScript notes

Links

​Linkup /fetch integration guide

​When to use it

​Setup

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

​Tool definition (OpenAI function-calling format)

​Operational guidance (inline)

​renderJs selection

​When to use Fetch

​The Search → Fetch pattern

​Constraints

​TypeScript notes

​Links

Linkup `/fetch` integration guide

When to use it

Setup

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

Tool definition (OpenAI function-calling format)

Operational guidance (inline)

`renderJs` selection

When to use Fetch

The Search → Fetch pattern

Constraints

TypeScript notes

Links