Unstructured llms.txt · AI Docs Browser · mdream

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# Unstructured llms.txt

docs.unstructured.io/llms.txt

[Raw llms.txt](https://docs.unstructured.io/llms.txt) [Raw llms-full.txt](https://docs.unstructured.io/llms-full.txt)

Copy Markdown [](https://docs.unstructured.io/llms.txt)

llms.txt

Docs

About Unstructured

Create destination connector

Create destination connection check

Delete destination connector

Destination endpoints

Get destination connector

Get destination connection check

List destination connectors

Update destination connector

Cancel job

Create job

Download job output

Get job

Get job details

Get job failed files

Job endpoints

List jobs

Create notification channel

Delete notification channel

Get notification

Get notification channel

Get notifications unread count

List notification channels

List notifications

Mark notifications read

Notification endpoints

Update notification channel

Verify notification channel

Create source connector

Create source connection check

Delete source connector

Get source connector

Get source connection check

List source connectors

Source endpoints

Update source connector

Get template

List templates

Template endpoints

Create workflow

Create workflow notification channel

Delete workflow

Delete workflow notification channel

Get workflow

Get workflow notification channel

List workflow notification channels

List workflows

Run workflow

Update workflow

Update workflow notification channel

Verify workflow notification channel

Workflow endpoints

Email Notifications

Unstructured API on AWS

Unstructured API on Azure

Overview

Partition Endpoint parameters

Endpoint errors

Chunking strategies

Document elements and metadata

Examples

Extract images and tables from documents

Generate a JSON schema for a file

Get chunked elements

Get element contents

Overview

Partitioning strategies

Process an individual file by making a direct POST request

Unstructured API Quickstart

JavaScript/TypeScript SDK

Python SDK

Speed up processing of large files and batches

Extract tables as HTML

Transform a JSON file into a different schema

Overview

Embed quickstart

Enrich quickstart

Extract quickstart

Unstructured API quickstart

Transform quickstart

Supported file types

Troubleshooting Unstructured API keys and URLs

Webhooks

Astra DB

Azure AI Search

Azure Blob Storage

Couchbase

Delta Tables in Databricks

Databricks Volumes

Delta Tables in Amazon S3

Elasticsearch

IBM FileNet

Google Cloud Storage

IBM watsonx.data

Kafka

Local

Milvus

MongoDB

MotherDuck

Neo4j

OneDrive

OpenSearch

Overview

Pinecone

PostgreSQL

Qdrant

Redis

S3

Snowflake

Teradata

Teradata Enterprise Vector Store

VAST

Weaviate

Errors

Jobs

Migration

Available models

Contextual chunking node

Chunk by Table Merging strategy

Embedder node

Enhancement nodes

LLM extraction

Regex extraction

Generative OCR task

Image Description task

Named Entity Recognition (NER) task

Table Description task

Table to HTML task

Custom workflow DAG nodes

Chunk by Character strategy

Chunk by Page strategy

Chunk by Similarity strategy

Chunk by Title strategy

Auto partition strategy

Fast partition strategy

High Res partition strategy

VLM partition strategy

Transform nodes

Overview

Retries

Azure Blob Storage

Box

Confluence

Couchbase

Databricks Volumes

Dropbox

Elasticsearch

IBM FileNet

Google Cloud Storage

Google Drive

Jira

Kafka

Local

MongoDB

Microsoft OneDrive

OpenSearch

Outlook

Overview

PostgreSQL

S3

Salesforce

Microsoft SharePoint

Slack

Snowflake

Teradata

VAST

Zendesk

Workflows

AI providers

Connecting to customer-managed services on AWS

Connecting to AWS-managed services

Connector support for AWS PrivateLink

Configure DNS for AWS PrivateLink

Onboarding your dedicated instance + AWS PrivateLink

Enterprise Connect for AWS

Enterprise Connect for Amazon Bedrock

Enterprise Connect for AWS connectors

Onboarding in-VPC on your AWS platform

Unstructured Business on Amazon Web Services (AWS)

Connecting to customer-managed services on Azure

Connecting to Azure-managed services

Connector support for Azure Private Link

Configure DNS for Azure Private Link

Onboarding Dedicated Instance + Azure Private Link

Enterprise Connect for Azure

Onboarding in-VPC on your Microsoft Azure platform

Unstructured Business on Microsoft Azure (Azure)

Concepts and architecture

Before you begin

Dedicated instance overview

Requirements and limitations

Security FAQ

Security model

Shared responsibility model

Onboarding in-VPC on your Google Cloud Platform (GCP)

Unstructured Business in-VPC on Google Cloud Platform (GCP) - overview

Configure an identity provider

IdP group mappings

IdP overview

Unstructured Business

Security and compliance overview

Chunking

Document elements and metadata

Embedding

Generative OCR optimization

Image descriptions

Named entity recognition (NER)

Overview

Table descriptions

Tables to HTML

More examples

Unstructured concepts overview

Partitioning

Additional examples

Choose an extraction method: LLM or Regex

Structured data extraction

Structured Extraction with LLM

Structured Extraction with Regex

Saving extracted data

Using the structured data extractor

Query processed PDF with HuggingChat

Table extraction from PDF

Multi-file API processing

Delta Table source connector

Vector database ingestion

Notebooks

Azure Blob Storage event triggers

Claude Desktop

CrewAI

Databricks Volumes event triggers

Firecrawl

Google Cloud Storage event triggers

Google Drive event triggers

IBM watsonx Orchestrate

Query JSON with jq

Working with Unstructured JSON output

Langflow

Model Context Protocol (MCP) Hands-On Walkthrough for the Unstructured Pipeline API

Model Context Protocol (MCP) Hands-On Walkthrough for the Unstructured Partition Endpoint

Chatbot with Neo4j

OneDrive event triggers

PII detection

Amazon S3 event triggers

Amazon S3 Vectors

SharePoint event triggers

Streamlit in Snowflake

VectorShift

Frequently asked questions

Unstructured Foundation installation for Claude Code

Unstructured Foundation installation for Claude Desktop

Unstructured Foundation installation for the Codex CLI

Unstructured Foundation installation for Codex Desktop

Unstructured Foundation installation for the Cursor CLI

Unstructured Foundation installation for the Cursor IDE

Get started with Unstructured Foundation

The Unstructured Foundation MCP server

Unstructured Foundation overview

Get started with Unstructured Foundation

Unstructured Foundation sources

Unstructured Foundation storage

Supported file types

Troubleshoot Unstructured Foundation

Chunking

Embedding

Document elements and metadata

Models

Partitioning strategies

Chunking

Cleaning

Embedding

Extracting

Core Functionality

Partitioning

Staging

Set embedding behavior

Examples

Extract images and tables from documents

Process a subset of files

Get chunked elements

Get element contents

Set the OCR agent

Speed up processing of large files and batches

Extract tables as HTML

Astra DB

Azure

Azure AI Search

Box

Chroma

Couchbase

Delta Tables in Databricks

Databricks Volumes

Delta Tables in Amazon S3

Dropbox

DuckDB

Elasticsearch

Google Cloud Storage

IBM watsonx.data

Kafka

KDB.AI

LanceDB

Local

Milvus

MongoDB

MotherDuck

Neo4j

OneDrive

OpenSearch

Overview

Pinecone

PostgreSQL

Qdrant

Redis

S3

SFTP

SingleStore

Snowflake

SQLite

Teradata

Vectara

Weaviate

Process files in batches by using the Unstructured Ingest CLI

Chunking configuration

Embedding configuration

Overview

Partition configuration

Processor configuration

Ingest dependencies

Overview

Process files in batches by using the Unstructured Ingest Python library

Airtable

Astra DB

Azure

Box

Confluence

Couchbase

Databricks Volumes

Delta Table

Discord

Dropbox

Elasticsearch

GitHub

GitLab

Google Cloud Storage

Google Drive

Jira

Kafka

Local

MongoDB

Notion

OneDrive

OpenSearch

Outlook

Overview

PostgreSQL

S3

Salesforce

SFTP

SharePoint

SingleStore

Slack

Snowflake

SQLite

Teradata

Zendesk

Supported file types

Docker installation

Full installation

Overview

staging functions

Overview

Quickstart

Supported file types

Account API keys and API URLs

Account billing

Organizational accounts

Accounts overview

Role-based access control (RBAC)

Account usage

Workspaces

Supported connectors

Astra DB

Azure AI Search

Azure Blob Storage

Couchbase

Delta Tables in Databricks

Databricks Volumes

Delta Tables in Amazon S3

Elasticsearch

IBM FileNet

Google Cloud Storage

IBM watsonx.data

Kafka

Milvus

MongoDB

MotherDuck

Neo4j

OneDrive

OpenSearch

Overview

Pinecone

Pinecone destination connector quickstart

PostgreSQL

Qdrant

Redis

S3

Snowflake

Teradata

Teradata Enterprise Vector Store

VAST

Weaviate

Jobs

Overview

Unstructured Pipelines quickstarts

Azure Blob Storage

Box

Confluence

Couchbase

Databricks Volumes

Dropbox

Dropbox source connector quickstart

Elasticsearch

IBM FileNet

Google Cloud Storage

Google Drive

Jira

Kafka

MongoDB

Microsoft OneDrive

OpenSearch

Outlook

Overview

PostgreSQL

S3

Salesforce

Microsoft SharePoint

Slack

Snowflake

Teradata

VAST

Zendesk

Supported file types

Unstructured Pipelines walkthrough

Webhooks

Workflows

Access to services

Delete or export personal data stored by Unstructured

Raise an invoice issue or request a refund

Overview

Google Drive source connectors cannot be created by using the API

Authorization and permissions issues

S3 destination connector - Unable to locate credentials

Configuration and resource issues

Data format, schema, and validation issues

Document processing issues

Unable to sign up with personal email address

Get authenticated user error

Google Drive schema validation failure

Internal issues

Network, connection, and timeout issues

The Fast strategy is not available for image files

Overview

Quota, billing, and rate limiting issues

Workflow already has a job scheduled or in progress

Requesting support

Shared Responsibility Model

Check service status

Unstructured Transform billing

Unstructured Transform MCP sample code generation

Unstructured Transform MCP server installation for the Google Antigravity CLI

Unstructured Transform MCP server installation for Google Antigravity Desktop

Unstructured Transform MCP server installation for Claude Code

Unstructured Transform MCP server installation for Claude Desktop

Unstructured Transform MCP server installation for Cline

Unstructured Transform MCP server installation for the Codex CLI

Unstructured Transform MCP server installation for Codex Desktop

Unstructured Transform MCP server installation for the Cursor CLI

Unstructured Transform MCP server installation for the Cursor IDE

Unstructured Transform MCP server installation for DSPy

Unstructured Transform MCP server installation for Dust

Unstructured Transform MCP server installation for the Gemini CLI

Unstructured Transform MCP server installation for Firebase Genkit

Unstructured Transform MCP server installation for Google ADK

Unstructured Transform MCP server installation for Goose

Unstructured Transform MCP server installation for Gumloop

Unstructured Transform MCP server installation for LangChain and LangGraph

Unstructured Transform MCP server installation for Mastra

Unstructured Transform MCP server installation for Microsoft Agent Framework

Unstructured Transform MCP server installation for NVIDIA NeMo Agent Toolkit

Get started with the Unstructured Transform MCP server

Unstructured Transform MCP server installation for Pydantic AI

Unstructured Transform MCP server installation for Vercel AI SDK

Unstructured Transform MCP file parsing options

Unstructured Transform Overview

Unstructured Transform MCP prompting strategies

Unstructured Transform MCP server quickstart

Supported file types for Unstructured Transform

Welcome to Unstructured!

Optional

Get support

Service status

Feedback

Blog

Product info

Trust portal

Contact Sales (e-mail)

Meta-prompt (titles)

Meta-prompt (full)

## What is Unstructured's llms.txt?

Unstructured publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Unstructured offers and where to find details.

Pass

Spec

2

Sections

506

Links

69.3 KB

Size

~17.7k

Tokens

Sections: Docs · Optional

## Add Unstructured Docs to Your AI Assistant

Select your tool to see how to add Unstructured's llms.txt as a documentation source.

Cursor

 Windsurf

 Claude Code

 ChatGPT

 Zed

 Copilot

1. 1

   Open any chat or composer panel
2. 2

   Type @Docs and select "Add new doc"
3. 3

   Paste the URL: https://docs.unstructured.io/llms.txt
4. 4

   Wait for the green dot (indexing complete)
5. 5

   Reference @Docs in chat when asking about Unstructured

Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too.

## Spec Compliance 6 notes

## Frequently Asked Questions

Where is Unstructured's llms.txt file?

Unstructured publishes its llms.txt at https://docs.unstructured.io/llms.txt. This file provides a structured, markdown-formatted index of Unstructured's documentation that AI systems can consume to understand the project's APIs, guides, and references.

How do I use Unstructured's llms.txt with AI coding assistants?

Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Unstructured's documentation so it can provide better code suggestions and answers about Unstructured.

What does Unstructured's llms.txt contain?

Unstructured's llms.txt contains 2 sections and 506 documentation links in 69.3 KB (~17.7k tokens). Key sections include Docs, Optional.

How many tokens does Unstructured's llms.txt use?

The concise llms.txt index is approximately 17.7k tokens (69.3 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline.

Can I generate an llms.txt for my own project?

Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator.

## Browse More llms.txt Files

[Zapier](https://mdream.dev/llms-txt/unstructured/llms-txt/zapier) [Velt](https://mdream.dev/llms-txt/unstructured/llms-txt/velt) [Hyperline](https://mdream.dev/llms-txt/unstructured/llms-txt/hyperline) [Meilisearch Documentation](https://mdream.dev/llms-txt/unstructured/llms-txt/meilisearch-documentation) [Method API Docs](https://mdream.dev/llms-txt/unstructured/llms-txt/method-api-docs) [Mangopay docs](https://mdream.dev/llms-txt/unstructured/llms-txt/mangopay-docs) [Bytebase Docs](https://mdream.dev/llms-txt/unstructured/llms-txt/bytebase-docs) [Junction](https://mdream.dev/llms-txt/unstructured/llms-txt/junction)

[View all 99 projects ](https://mdream.dev/llms-txt/unstructured/llms-txt)

## Related Tools

[<h3>llms.txt Generator</h3>Generate an llms.txt for your own project.](https://mdream.dev/llms-txt/unstructured/tools/llms-txt/generator) [<h3>llms.txt Validator</h3>Validate your llms.txt against the official spec.](https://mdream.dev/llms-txt/unstructured/tools/llms-txt/validator)

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