Storage
Storage in LlamaIndex.TS works automatically once you’ve configured a
StorageContext object.
Per default a local directory is used for storage. Depening on the storage type (i.e. doc stores, index stores or vector stores), you can configure a different persistence layer. Most commonly a vector database is used as vector store.
Local Storage
Section titled “Local Storage”You can configure the persistDir to define where to store the data locally.
import { Document, VectorStoreIndex, storageContextFromDefaults,} from "llamaindex";
const storageContext = await storageContextFromDefaults({ persistDir: "./storage",});
const document = new Document({ text: "Test Text" });const index = await VectorStoreIndex.fromDocuments([document], { storageContext,});API Reference
Section titled “API Reference”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/