Multi-AI agent router: compare OpenAI, Anthropic & Groq responses with webhooks

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Introduction This workflow connects to OpenAI, Anthropic, and Groq, processing requests in parallel with automatic performance metrics. Ideal for testing speed, cost, and quality across models. How...

Best for

Engineering automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.webhook, n8n-nodes-base.set, n8n-nodes-base.code, n8n-nodes-base.switch, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.merge, n8n-nodes-base.respondtowebhook

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title: Multi-AI agent router: compare OpenAI, Anthropic & Groq responses with webhooks
Workflow name: Multi-AI agent router: compare OpenAI, Anthropic & Groq responses with webhooks

Introduction

This workflow connects to OpenAI, Anthropic, and Groq, processing requests in parallel with automatic performance metrics. Ideal for testing speed, cost, and quality across models.

How It Works

Webhooks trigger parameter extraction and routing. Three AI agents run simultaneously with memory and parsing. Responses merge with detailed metrics.

Workflow Template

Webhook → Extract Parameters → Router ├→ OpenAI Agent ├→ Anthropic Agent ├→ Groq Agent → Merge → Metrics → Respond

Workflow Steps

Webhook receives POST with prompt and settings.
Parameters extracted and validated.
Router directs by cost, latency, or type.
AI agents run in parallel.
Results merged with metadata.
Metrics compute time, cost, and quality.
Response returns outputs and recommendation.

Setup Instructions

Activate Webhook with authentication.
Add API keys for all providers.
Define models, tokens, and temperature.
Adjust Router logic for selection.
Tune Metrics scoring formulas.

Prerequisites

n8n v1.0+ instance
API keys: OpenAI, Anthropic, Groq
HTTP client for testing

Customization

Add providers like Gemini or Azure OpenAI. Enable routing by cost or performance.

Benefits

Auto-select efficient providers and compare model performance in real time.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 2 - Output Parser2

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 3 - Webhook

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2

Block 4 - Extract Input Parameters

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 5 - Dynamic LLM Router

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 6 - Route to Provider

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 7 - OpenAI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.7

Block 8 - Anthropic Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.7

Block 9 - Groq Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.7

Block 10 - Merge Results

Type / Role: n8n-nodes-base.merge - merge
Config choices: Version 3

Block 11 - Calculate Performance Metrics

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 12 - Respond to Webhook

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.1

Block 13 - OpenAI Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1

Block 14 - Output Parser1

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 15 - Groq Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGroq - lmChatGroq
Config choices: Version 1

Block 16 - Anthropic Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatAnthropic - lmChatAnthropic
Config choices: Version 1

Block 17 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 18 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Multi-AI agent router: compare OpenAI, Anthropic & Groq responses with webhooks
Complexity	advanced
Nodes	18
Categories	Engineering, AI Summarization
Author	Cheng Siong Chin
Published	29 Oct 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/10287/10287.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Engineering workflows AI Summarization workflows

Frequently asked questions

What does Multi-AI agent router: compare OpenAI, Anthropic & Groq responses with webhooks do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI Summarization use case.

Cheng Siong Chin

203 workflows

Nodes

@n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.webhook n8n-nodes-base.set n8n-nodes-base.code n8n-nodes-base.switch @n8n/n8n-nodes-langchain.agent n8n-nodes-base.merge n8n-nodes-base.respondtowebhook

Complexity

advanced

Published 29 Oct 2025

Likes 0

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Install path: /data/workflows/10287/10287.json

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Multi-AI agent router: compare OpenAI, Anthropic & Groq responses with webhooks

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Introduction

How It Works

Workflow Template

Workflow Steps

Setup Instructions

Prerequisites

Customization

Benefits

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Output Parser

Block 2 - Output Parser2

Block 3 - Webhook

Block 4 - Extract Input Parameters

Block 5 - Dynamic LLM Router

Block 6 - Route to Provider

Block 7 - OpenAI Agent

Block 8 - Anthropic Agent

Block 9 - Groq Agent

Block 10 - Merge Results

Block 11 - Calculate Performance Metrics

Block 12 - Respond to Webhook

Block 13 - OpenAI Model

Block 14 - Output Parser1

Block 15 - Groq Model

Block 16 - Anthropic Model

Block 17 - Sticky Note

Block 18 - Sticky Note1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions