Data Connectors (LlamaHub)
Concept
Section titled “Concept”A data connector (aka Reader) ingest data from different data sources and data formats into a simple Document representation (text and simple metadata).
LlamaHub
Section titled “LlamaHub”Our data connectors are offered through LlamaHub 🦙. LlamaHub is an open-source repository containing data loaders that you can easily plug and play into any LlamaIndex application.
Usage Pattern
Section titled “Usage Pattern”Get started with:
from llama_index.core import download_loader
from llama_index.readers.google import GoogleDocsReader
loader = GoogleDocsReader()documents = loader.load_data(document_ids=[...])See the full usage pattern guide for more details.
Modules
Section titled “Modules”Some sample data connectors:
- local file directory (
SimpleDirectoryReader). Can support parsing a wide range of file types:.pdf,.jpg,.png,.docx, etc. - Notion (
NotionPageReader) - Google Docs (
GoogleDocsReader) - Slack (
SlackReader) - Discord (
DiscordReader) - Apify Actors (
ApifyActor). Can crawl the web, scrape webpages, extract text content, download files including.pdf,.jpg,.png,.docx, etc.
See the modules guide for more details.
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/