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Enhance Chat Responses with Real-Time Search Data via Bright Data & Gemini AI

Configured with Agent, Chat Trigger, LM Chat Google Gemini, Mcp Client, and additional nodes. Review the connections and setup before adapting this template.

Workflow preview
TriggerWhen chat messagereceivedChat TriggerAI & modelsAI AgentAgentAI & modelsGoogle Gemini ChatModelLM Chat Google GeminiData storeSimple MemoryMemory Buffer WindowTriggerWhen clicking ‘Testworkflow’Manual TriggerIntegrationMCP Client list alltools for Bright DataMcp ClientIntegrationMCP Client Bright DataSearch ToolMcp ClientTransformSet search queryEdit FieldsIntegrationGoogle Search Enginefor Bright DataMcp Client ToolIntegrationBing Search Engine forBright DataMcp Client ToolIntegrationMCP Client List alltoolsMcp Client ToolWeb / APIHTTP Request forWebhook NotificationTool Http RequestIntegrationYandex Search Enginefor Bright DataMcp Client Tool

Node categories in this workflow

  • Trigger
  • AI & models
  • Data store
  • Integration
  • Transform
  • Web / API

Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.

Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.

How it works

The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.

Workflow node names, types, and operations
NodeCategoryTypeOperation
When chat message receivedTriggerChat TriggerSee node parameters
AI AgentAI & modelsAgentSee node parameters
Google Gemini Chat ModelAI & modelsLM Chat Google GeminiSee node parameters
Simple MemoryData storeMemory Buffer WindowSee node parameters
When clicking ‘Test workflow’TriggerManual TriggerSee node parameters
MCP Client list all tools for Bright DataIntegrationMcp ClientSee node parameters
MCP Client Bright Data Search ToolIntegrationMcp ClientexecuteTool
Set search queryTransformEdit FieldsSee node parameters
Google Search Engine for Bright DataIntegrationMcp Client ToolexecuteTool
Bing Search Engine for Bright DataIntegrationMcp Client ToolexecuteTool
MCP Client List all toolsIntegrationMcp Client ToolSee node parameters
HTTP Request for Webhook NotificationWeb / APITool Http RequestPOST
Yandex Search Engine for Bright DataIntegrationMcp Client ToolexecuteTool

Setup

  1. Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
  2. Connect your own credentials through n8n’s credential store. Replace REPLACE_WITH_* values with your resource identifiers.
  3. Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
  4. Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.

Requirements

An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.

Credential types declared in the source

  • googlePalmApi
  • mcpClientApi

Workflow notes

Google Search Engine for Bright Data

Scrape search results from Google, Bing or Yandex. Returns SERP results in markdown (URL, title, description)

Disclaimer

Disclaimer

This template is only available on n8n self-hosted as it's making use of the community node for MCP Client.

Note

Note

Use Bright Data MCP Search Engine assistant tools to perform Google, Bing or Yandex Search.

The AI Agent will make use of suitable search engine-based tools, returns the response to Chat and also performs the Webhook notification call for sending the AI responses via the MCP Client tools.

Source - https://github.com/luminati-io/brightdata-mcp

LLM Usage

LLM Usage

Google Gemini is employed by the AI agent to understand and interpret user queries. Based on this interpretation, the agent initiates a call to the appropriate MCP client to perform the required web search task.

Enhance Chat Responses with Real-Time Search Data via Bright Data & Gemini AI

Enhance Chat Responses with Real-Time Search Data via Bright Data & Gemini AI

Purpose and structure

This folder contains the Enhance Chat Responses with Real-Time Search Data via Bright Data & Gemini AI workflow. Its executable nodes use agent, chatTrigger, lmChatGoogleGemini, manualTrigger, mcpClient, mcpClientTool, memoryBufferWindow, set, toolHttpRequest. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.

Setup

Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.

Entry points

When chat message received, When clicking ‘Test workflow’

Verification

Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.

Attribution

https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Manual/1183_Manual_Stickynote_Automation_Webhook.json MIT; preserve source notices.

Canvas section labels

These name areas of the original canvas; they do not include explanatory instructions.

  • Bright Data Search Engines
  • Bright Data Google Search

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