Generate research proposals with GPT-4o, web search, and quality control agents

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1. Workflow Overview

How It Works This workflow automates academic and professional research proposal generation using a multi agent AI pipeline. It targets researchers, academics, grant writers, and R&D teams who need...

Best for

Content Creation automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.manualtrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.agenttool, n8n-nodes-base.httprequesttool, @n8n/n8n-nodes-langchain.toolserpapi, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.if

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: Generate research proposals with GPT-4o, web search, and quality control agents
Workflow name: Generate research proposals with GPT-4o, web search, and quality control agents

How It Works

This workflow automates academic and professional research proposal generation using a multi-agent AI pipeline. It targets researchers, academics, grant writers, and R&D teams who need structured, high-quality proposals efficiently. The core problem it solves: manually drafting proposals is time-consuming, inconsistent, and prone to missing key elements like ethics, impact, and funding alignment. A Supervisor Agent orchestrates three specialist sub-agents, Research Content, Strategic Planning, and Ethics/Impact, each powered by dedicated AI models. A Funding Agency Research Tool and Web Search Tool supply real-time context. The generated proposal is parsed, then evaluated by a Quality Control Agent. Proposals meeting the quality threshold are formatted and stored; those falling short are flagged for human revision, ensuring only polished outputs reach storage.

Setup Steps

Add OpenAI (or compatible) API credentials to all AI model nodes.
Configure Supervisor, Research Content, Strategic Planning, and QC Agent system prompts.
Set up Funding Agency Research Tool with target agency endpoints or search parameters.
Connect Web Search Tool credentials (e.g., SerpAPI or Tavily).
Configure storage node (Google Sheets/database) with target schema.
Set quality score threshold in the Check Quality Score node.

Prerequisites

Web search API key (SerpAPI/Tavily)
Google Sheets or database credentials

Use Cases

Grant proposal drafting for research institutions

Customisation

Swap AI models per agent for cost/performance balance

Benefits

Cuts proposal drafting time by 70–80%

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 - Start Proposal Generation

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

Block 2 - Supervisor Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 3 - Supervisor Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 4 - Research Content Agent

Type / Role: @n8n/n8n-nodes-langchain.agentTool - agentTool
Config choices: Version 3

Block 5 - Research Content Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 6 - Strategic Planning Agent

Type / Role: @n8n/n8n-nodes-langchain.agentTool - agentTool
Config choices: Version 3

Block 7 - Strategic Planning Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 8 - Funding Agency Research Tool

Type / Role: n8n-nodes-base.httpRequestTool - httpRequestTool
Config choices: Version 4.4

Block 9 - Web Search Tool

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

Block 10 - Quality Control Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 11 - Quality Control Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 12 - Quality Assessment Output

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 13 - Check Quality Score

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.3

Block 14 - Format Final Proposal

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

Block 15 - Flag for Revision

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

Block 16 - Store Proposal Results

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

Block 17 - Prepare Storage Data

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

Block 18 - Conversation Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 19 - Ethics Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 20 - Impact Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.3

Block 21 - Parse Proposal Structure

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

Block 22 - Sticky Note

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

Block 23 - Sticky Note1

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

Block 24 - Sticky Note2

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

Showing the first 24 of 27 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Generate research proposals with GPT-4o, web search, and quality control agents
Complexity	advanced
Nodes	27
Categories	Content Creation, AI Summarization
Author	Cheng Siong Chin
Published	04 Mar 2026

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/13869/13869.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 Content Creation workflows AI Summarization workflows

Frequently asked questions

What does Generate research proposals with GPT-4o, web search, and quality control agents 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 Content Creation, AI Summarization use case.

Cheng Siong Chin

203 workflows

Nodes

n8n-nodes-base.manualtrigger @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.agenttool n8n-nodes-base.httprequesttool @n8n/n8n-nodes-langchain.toolserpapi @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.if

Complexity

advanced

Published 04 Mar 2026

Likes 0

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Install path: /data/workflows/13869/13869.json

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Generate research proposals with GPT-4o, web search, and quality control agents

Workflow preview

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How It Works

Setup Steps

Prerequisites

Use Cases

Customisation

Benefits

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Start Proposal Generation

Block 2 - Supervisor Agent

Block 3 - Supervisor Model

Block 4 - Research Content Agent

Block 5 - Research Content Model

Block 6 - Strategic Planning Agent

Block 7 - Strategic Planning Model

Block 8 - Funding Agency Research Tool

Block 9 - Web Search Tool

Block 10 - Quality Control Agent

Block 11 - Quality Control Model

Block 12 - Quality Assessment Output

Block 13 - Check Quality Score

Block 14 - Format Final Proposal

Block 15 - Flag for Revision

Block 16 - Store Proposal Results

Block 17 - Prepare Storage Data

Block 18 - Conversation Memory

Block 19 - Ethics Model

Block 20 - Impact Model

Block 21 - Parse Proposal Structure

Block 22 - Sticky Note

Block 23 - Sticky Note1

Block 24 - Sticky Note2

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