Document Stores
Document stores contain ingested document chunks, i.e. Nodes.
Available Document Stores
Section titled “Available Document Stores”- SimpleDocumentStore: A simple in-memory document store with support for persisting data to disk.
- PostgresDocumentStore: A PostgreSQL document store, see PostgreSQL Storage.
Check the LlamaIndexTS Github for the most up to date overview of integrations.
Using PostgreSQL as Document Store
Section titled “Using PostgreSQL as Document Store”npm i llamaindex @llamaindex/postgresYou can configure the schemaName, tableName, namespace, and
connectionString. If a connectionString is not
provided, it will use the environment variables PGHOST, PGUSER,
PGPASSWORD, PGDATABASE and PGPORT.
import { Document, VectorStoreIndex, storageContextFromDefaults } from "llamaindex";import { PostgresDocumentStore } from "@llamaindex/postgres";
const storageContext = await storageContextFromDefaults({ docStore: new PostgresDocumentStore(),});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/