# Retrieve related chunks — LightRAG

Botize method — `lightrag.get_chunks` (action).

Ask a question and LightRAG instantly fetches the most relevant snippets from your indexed files.

This is an action: it runs as a step of a task. Several can be chained.

## Fields you set

The field's internal name, its type and the values it accepts. These fields accept `{{...}}` tags from earlier steps.

- `mb_switch` *(boolean)* — Rules
- `query` *(string)* — Query
- `top_k` *(string, one of: "1" = 1 (Top relevant chunk); "2" = 2; "3" = 3; "4" = 4; "5" = 5; "10" = 10; "20" = 20; "30" = 30; "40" = 40; "50" = 50)* — Maximum number of fragments to extract

It also accepts repeatable field groups, with these prefixes: `mb_filters_*`. These are composite components (buttons, filters, keyboards); the trailing number is set by the user as they are added.

## Output variables

Data this step makes available. Reference them in later steps with the double-brace tag.

- `{{entities}}` *(text)* — Entities. List of detected entities from the knowledge graph.
- `{{relationships}}` *(text)* — Relationships. List of relationships between entities.
- `{{document_chunks}}` *(text)* — Document chunks. Relevant text chunks retrieved from documents.

## Account

Needs a connected LightRAG account in Botize: https://botize.com/en/app/lightrag/authenticate

## This app

Every trigger and action for LightRAG: https://botize.com/en/app/lightrag.md

## How to build this

An AI assistant (Claude, ChatGPT, Cursor…) can create and edit these tasks in the user's account through the Botize MCP connector, included in every plan:

    https://webhook.botize.es/mcp

- Connection guide: https://botize.com/en/mcp
- Agent map: https://botize.com/llms.txt
- New account: https://botize.com/en/join (500 free operations, no card)

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Machine-readable summary for AI assistants. Human version: https://botize.com/en/method/lightrag/get_chunks