As a solopreneur, you constantly juggle tasks.
You know AI can provide a competitive edge, but the idea of committing to another monthly subscription before you've even confirmed its value is a major roadblock.
The time spent switching between Wikipedia, Google, and ChatGPT to research a client project is time you can't bill for, disrupting your focus and slowing you down.
This guide solves that.
We'll build a custom AI research assistant that you own and control.
It integrates directly into your workflow, maintains conversation context, and operates on a pay-per-use model, eliminating costly subscription fees.
✅ What You'll Accomplish
✔️ Create a custom AI research assistant with conversation memory
✔️ Integrate Wikipedia and web search capabilities for comprehensive research
✔️ Build a pay-per-use system that eliminates monthly subscription costs
✔️ Deploy a scalable foundation for advanced AI automation workflows
🧰 What You Need Before Starting
Skill level: Beginner
Required accounts/tools:
An n8n instance (cloud or self-hosted)
An OpenAI API account for language model access (pay-per-use)
Optional: A SerpAPI account for real-time web search capabilities
Time Investment: 25-35 minutes for initial setup
Helpful preparation: Download the complete n8n workflow file here to get started: [AI_Chatbot_Tool_Integration.json]
Step 1: Create the n8n Workflow
Objective: Create the container for your AI assistant in your n8n workspace.
Action items:
Open your n8n instance and create a new workflow
Name it something memorable like "AI Business Assistant"
Set execution order to v1
Enable auto-save to prevent losing your work
Key points:
A stable n8n instance is crucial for reliable operation
Test your n8n setup with a simple workflow before building the AI assistant
✅ Checkpoint: You have a new, blank workflow saved and ready for building.
Step 2: Configure the OpenAI Node
Objective: Connect your workflow to the GPT-4o model, which will act as the "brain" of your assistant.
Action items:
Add an OpenAI Chat Model node to your workflow
Select your pre-configured OpenAI API credentials
Choose gpt-4.1 for a strong balance of capability and cost
Set temperature to 0.3 for more factual, less creative responses suitable for business research
Test the node with a simple prompt like "Hello" to verify connection
Key points:
Temperature setting controls output consistency - lower values produce more deterministic results
Authentication errors usually mean incorrect API key or insufficient OpenAI account funds
✅ Checkpoint: The OpenAI node executes successfully and returns appropriate responses to test prompts.
Step 3: Add Information-Gathering Tools
Objective: Give your assistant the ability to access external knowledge sources through Wikipedia and optional web search.
Action items:
Add a Define Tools node to your workflow
Enable the Wikipedia tool (requires no additional API key)
Add the SerpAPI tool but keep it disabled initially
Connect the Define Tools node output to prepare for the AI Agent integration
Key points:
Wikipedia provides reliable, encyclopedic information for factual queries
The AI will intelligently choose which tool to use based on your query type
✅ Checkpoint: The Wikipedia tool is visible and enabled, ready for integration with the AI Agent node.
Step 4: Implement Conversation Memory
Objective: Enable your assistant to remember conversation context for more natural, productive interactions.
Action items:
Add a Window Buffer Memory node to your workflow
Set Memory Key to "memory"
Configure Session ID as ={{ $json.sessionId }} to keep conversations separate
Set Context Window to 20 messages for balanced context retention and cost management
Connect the memory node to prepare for AI Agent integration
Key points:
Session ID prevents conversation mixing in multi-user environments
Context window size affects both memory capability and processing costs
✅ Checkpoint: The memory system is configured and ready to maintain conversation context across multiple exchanges.
Step 5: Set Up the Central AI Agent
Objective: Create the central hub that connects your prompt, tools, and memory into a single, intelligent system.
Action items:
Add an AI Agent node as the central workflow coordinator
Map the input to user messages using ={{ $json.input }}
Connect the Define Tools node output to the AI Agent
Connect the Window Buffer Memory node output to the AI Agent
Test the complete workflow with a factual question to verify tool integration
Key points:
This node orchestrates the entire process, deciding whether to answer directly, use tools, or draw from memory
Input expression formatting must be exact: ={{ $json.input }}
✅ Checkpoint: The workflow runs end-to-end, with questions like "What is n8n?" triggering the Wikipedia tool and returning summarized answers.
Step 6: Enable Advanced Web Search (Optional)
Objective: Add current events and real-time data capabilities through web search integration.
Action items:
Sign up for an account at serpapi.com and obtain your API key
In n8n, go to Credentials and add a new SerpAPI credential with your key
Return to your workflow and assign the new credentials to the SerpAPI tool node
Enable the toggle switch on the SerpAPI node
Test with a current events question to verify web search functionality
Key points:
SerpAPI is a metered service - monitor usage in your dashboard to manage costs
Web search enables answers about recent events and real-time information
✅ Checkpoint: Current event queries like "What were the top tech headlines this week?" successfully trigger the SerpAPI tool.
🔍 Testing Your AI Business Assistant
Validation steps:
Factual Query Test: Ask "What is photosynthesis?" to verify Wikipedia tool integration
Memory Test: Follow up with "Why is it important for the planet?" to check context awareness
Current Info Test: Ask "Who won the Best Picture award last night?" to test web search (if enabled)
Tool Selection Test: Verify the AI chooses appropriate tools based on query type
✅ Success criteria: The AI assistant handles factual research, maintains conversation context, and selects appropriate information sources based on query requirements.
💼 Start Building, Stop Subscribing
Quick recap:
✔️ Custom AI research assistant with conversation memory and tool integration
✔️ Pay-per-use model that eliminates costly monthly subscription fees
✔️ Flexible, scalable foundation for advanced AI automation workflows
✔️ Professional research capabilities without enterprise-level costs
Tools referenced: n8n, OpenAI GPT-4, Wikipedia API, SerpAPI
Download the complete workflow template: [AI_Chatbot_Tool_Integration.json]
Want to see a specific workflows? Leave a comment! I answer every comment.
Excellent example of a simple to build, useful workflow. Thanks for sharing!