# Legal Case Research Extractor, Data Miner with Bright Data MCP: n8n workflow

> Started by an event in a connected app. It calls services over plain HTTP rather than through connectors. It hands the judgement calls to Gemini.

Source: https://millionrounds.com/workflow/legal-case-research-extractor-data-miner-with-bright-data-mc (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [Research and reporting](https://millionrounds.com/workflows?category=Research+and+reporting#library)

# Legal Case Research Extractor, Data Miner with Bright Data MCP

Started by an event in a connected app. It calls services over plain HTTP rather than through connectors. It hands the judgement calls to Gemini. 16 steps, 2 loops or waits: a working afternoon to understand properly.

Medium Calls a model: Gemini

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Flegal-case-research-extractor-data-miner-with-bright-data-mc)

**16 steps** Medium: a working afternoon

**0** Branches: places the flow splits

**2** Loops or waits

**0** Services by connector: it calls them over plain HTTP

## The flow

Starts it 1 Model 5 Logic 5 Service 5

The steps in the order they run, from what starts it.

- 1 **When clicking ‘Test workflow’** Manual trigger *Starts it*
- 2 **Structured Output Parser** Output Parser Structured *Model*
- 3 **Google Gemini Chat Model For Case Data Extract** Lm Chat Google Gemini *Model*
- 4 **Google Gemini Chat Model for HTML to Textual Data Extract Within the Loop** Lm Chat Google Gemini *Model*
- 5 **List all tools for Bright Data** Mcp Client *Service*
- 6 **Case Extractor** Chain Llm *Model*
- 7 **HTML to Textual Data Extract Within Loop** Chain Llm *Model*
- 8 **Set the Legal Case Research URL** Set *Logic*
- 9 **Code to output the collection of cases** Code *Logic*
- 10 **Create a binary data for LinkedIn company info extract** Function *Logic*
- 11 **Webhook Notification for HTML to Textual Data Extract Within the Loop** Http Request *Service*
- 12 **Bright Data MCP Client For Legal Case Research** Mcp Client *Service*
- 13 **Loop Over Items** Split In Batches *Logic*
- 14 **Write the case content to disk** Read Write File *Service*
- 15 **Wait** Wait *Logic*
- 16 **Bright Data MCP Client For Legal Case Research Within Loop** Mcp Client *Service*

## How it's built

- **Starts on:** An event in a connected app
- **Steps:** 16, 2 loops or waits
- **Size:** Medium: a working afternoon
- **Connects to:** Nothing by connector; it calls services over plain HTTP
- **Model:** Gemini

## Questions

What does it need to run?

An n8n account, and a key for Gemini. You connect your own accounts after importing it; none are included.

What starts it?

It starts on an event in a connected app.

Does it use AI?

Yes. It calls Gemini. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Plan an afternoon. 16 steps is enough that you should read each one before running it.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 16 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Flegal-case-research-extractor-data-miner-with-bright-data-mc)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Workflows like it

Also research and reporting, with the same services where possible, closest in size first.

- [**AI Contract Report: Plain English Translation + Risk Score Email** 16 steps · calls a model · Gmail](https://millionrounds.com/workflow/ai-contract-report-plain-english-translation-risk-score-emai)
- [**AI news digest: Summarize top stories with DALL-E** 16 steps · calls a model · Telegram](https://millionrounds.com/workflow/ai-news-digest-summarize-top-stories-with-dall-e)
- [**Amazon price drop analysis with Decodo and OpenAI** 16 steps · calls a model · Google Sheets](https://millionrounds.com/workflow/amazon-price-drop-analysis-with-decodo-and-openai)
- [**Analyze customer feedback with Azure GPT-4 and Jira** 16 steps · calls a model · Gmail, Google Sheets](https://millionrounds.com/workflow/analyze-customer-feedback-with-azure-gpt-4-and-jira)
- [**Analyze incoming letters with Google Drive and OpenAI** 16 steps · calls a model · Google Drive, Google Sheets](https://millionrounds.com/workflow/analysiere-eingehende-briefe-mit-google-drive-openai)
- [**Audience problem keyword research workflow with OpenAI** 16 steps · calls a model · Google Sheets](https://millionrounds.com/workflow/audience-problem-keyword-research-workflow-with-openai)