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Guide
Parse
v1
Features

Webhook

Set webhook_url to have LlamaParse POST a completed job result as JSON (text, markdown, and per-page data) to your HTTPS endpoint when parsing finishes.

At the end of a LlamaParse job, you can chose to receive the result directly on one of your endpoint. You simply have to precise the URL of the webhook endpoint where the data should be sent.

The webhook_url parameter should be a valid URL that your application or service is set up to handle incoming data from.

There’s a few restriction on the webhook URL:

  • The protocol must be HTTPS.
  • The host must be a domain name rather than an IP address.
  • The URL must be less than 200 characters.

Data will be sent as a POST request with a JSON body and with the following format:

{
"txt": "raw text",
"md": "markdown text",
"json": [
{
"page": 1,
"text": "page 1 raw text",
"md": "page 1 markdown text",
"images": [
{
"name": "img_p0_1.png",
"height": 100,
"width": 100,
"x": 0,
"y": 0
}
]
}
],
"images": [
"img_p0_1.png"
]
}


To use the Webhooks, set webhook_url to your URL (https://example.com/webhook).

parser = LlamaParse(
webhook_url="https://example.com/webhook"
)
Note for AI agents: this documentation is built for programmatic access. - Overview of all docs: https://developers.llamaindex.ai/llms.txt - Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md - Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters. - A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/