Loading from LlamaCloud
Our enterprise service, LlamaCloud, allows you to store and query your data in a fully-managed, scalable, and secure environment. For a full explanation of how to use LlamaCloud, see the LlamaCloud documentation, in particular the framework integration guide.
Using LlamaCloud from LlamaIndex
Section titled “Using LlamaCloud from LlamaIndex”You can use LlamaCloud to connect to your data stores and automatically index them. Once an index is created, you can use it in just a few lines of code:
import osfrom llama_cloud_services import LlamaCloudIndex
os.environ["LLAMA_CLOUD_API_KEY"] = "llx-..."
index = LlamaCloudIndex("my_first_index", project_name="Default")query_engine = index.as_query_engine()answer = query_engine.query("Example query")It’s also possible to programmatically load documents into a LlamaCloud index; check the documentation 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/