How To Create a Local AI Agent in 7 min with Cursor AI (take my code)

AI Agent on Your Computer: A Detailed Summary

Key Concepts:

• AI Agent: A customizable program that can perform tasks based on instructions.
• Zapier: An AI orchestration platform that connects different applications and services.
• Webhooks: A way for applications to communicate with each other in real-time.
• Cursor AI: An AI-powered code editor.
• npm: Node Package Manager, used for running JavaScript projects.
• Localhost: The address of your own computer when running a server.
• Zap: An automated workflow created in Zapier.
• Agent Input Message: The command or instruction given to the AI agent.

Setting Up the Local AI Agent

1. Code Acquisition:
   • The project code is available on GitHub (link in the video description).
   • Download the code from the provided Git repository.
   • A separate video is linked for users unfamiliar with downloading open-source code.
2. Cursor AI Setup:
   • Open the downloaded code in Cursor AI.
   • Locate line 47 in the code.
   • This line contains the webhook URL that needs to be replaced.
3. Zapier Webhook Creation:
   • Create a new Zap in Zapier.
   • Set the trigger to "Webhook."
   • Choose "Catch Hook" as the trigger event.
   • Copy the generated Zapier webhook URL.
4. Webhook Integration:
   • Paste the copied Zapier webhook URL into line 47 of the code in Cursor AI, replacing the existing URL.
5. Running the Agent:
   • Open the terminal in Cursor AI (click the terminal icon).
   • Run the command npm start.
   • Once the agent is running, open localhost:3000 in your browser.
6. Troubleshooting:
   • A Google Doc (link in the description) provides step-by-step instructions for resolving common errors, including issues with npm.
   • The document includes commands for Windows, Linux, and Mac.

Creating an AI Agent in Zapier

1. Agent Creation:
   • In Zapier, navigate to "New Agents" and create a "Custom Agent."
   • Name the agent (e.g., "AI Agent Best").
   • Set the trigger to "On a Trigger Zap."
2. Agent Instructions:
   • The first instruction is: "You'll receive an agent input message, follow its command."
   • The second instruction is: "Here are the actions you can execute."
3. Adding Actions:
   • Use the "Insert Tools" option to add actions the agent can perform.
   • Examples include:
     • Gmail: Create Draft
     • Google Calendar: Create Detailed Event
     • Visit Website: Google Search
   • Actions are added line by line.
   • The agent's capabilities are limited to the actions defined here.
4. Zapier Automation Configuration:
   • In the Zapier automation, select "Agents" as the action.
   • Choose "Run Agent" as the action event.
   • Select the created AI agent (e.g., "AI Agent Best").
   • Set the "Agent Input Message" to come from the webhook data.
5. Testing and Publishing:
   • Use the test data from the code to test the trigger.
   • The command line input should appear in the test data.
   • Publish the Zap.

Example Use Case

1. Scenario: Create a draft email about going to dinner at a great place in San Francisco, using Google Search to find a top restaurant and including the link in the email. Send the email to [email protected].
2. Prompt: "Create a draft email about going to dinner in a great place in SF. Use Google Search to find a top restaurant and then provide that link in the email. Send it to [email protected]."
3. Result: The AI agent creates a draft email with the requested information, including a link to a list of top restaurants in San Francisco.

Synthesis/Conclusion

The video demonstrates how to create a local AI agent that can be customized to perform various tasks by integrating with Zapier. By setting up a webhook, connecting it to a Zapier automation, and defining the agent's actions, users can create powerful and personalized AI assistants that run directly on their computers. The key takeaway is the ability to combine different actions and leverage the vast integration capabilities of Zapier to automate complex workflows. The example use case highlights the potential of these agents to streamline tasks and improve productivity.