Runwork
StickyNote RssFeedReadTool HttpRequestTool Langchain.agent Langchain.chatTrigger Langchain.memoryBufferWindow +1 more

Build your first AI agent

This introductory workflow helps you create a functional AI agent using Google Gemini that can perform real-world tasks like fetching live weather and news. It features a simple chat interface and persistent memory to ensure natural, context-aware conversations. Perfect for beginners, it demonstrates how to transform a basic chatbot into an interactive assistant capable of taking direct action.

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What This Recipe Does

This automation transforms how teams gather and interact with industry information by creating a dedicated AI research assistant. Instead of manually checking various news sites or monitoring RSS feeds, business users can simply ask questions in a chat interface to receive synthesized, up-to-date insights. The agent combines live RSS data with custom web requests to provide a comprehensive view of any topic or competitor. This eliminates the manual labor associated with market research and ensures that decision-makers have access to the most current data available. By centralizing information retrieval into a conversational app, organizations can improve their response times to market shifts and identify emerging trends before they become mainstream. This tool is particularly valuable for teams that need to stay informed about fast-moving industries without spending hours on manual browsing. It bridges the gap between raw data sources and actionable intelligence, allowing your staff to focus on strategy rather than information gathering. The result is a more informed workforce and a significant reduction in the time spent on repetitive research tasks.

What You'll Get

Complete App

Forms, dashboards, and UI components ready to use

Automated Workflows

Background automations that run on your schedule

API Endpoints

REST APIs for external integrations

Connected Integrations

StickyNote, RssFeedReadTool, HttpRequestTool, Langchain.agent, Langchain.chatTrigger configured and ready

How It Works

  1. 1

    Click "Start Building" and connect your accounts

    Runwork will guide you through connecting StickyNote and RssFeedReadTool

  2. 2

    Describe any customizations you need

    The AI will adapt the recipe to your specific requirements

  3. 3

    Preview, test, and deploy

    Your app is ready to use in minutes, not weeks

Who Uses This

Frequently Asked Questions

Can I add my own specific news sources to this agent?

Yes, you can configure the RSS feed tool to point to any standard feed URL, allowing the AI to prioritize the sources most relevant to your business.

Does this require any coding knowledge to maintain?

No, once the initial feed URLs and API endpoints are connected, the AI handles the data extraction and synthesis automatically through the chat interface.

Can the agent pull data from websites that do not have an RSS feed?

Yes, the integrated HTTP request tool allows the assistant to fetch data from various web sources and APIs beyond standard news feeds.

What kind of output does the assistant provide?

The assistant provides natural language summaries, bulleted lists, or detailed reports based on the specific questions you ask in the chat.

Importing from n8n?

This recipe uses nodes like StickyNote, RssFeedReadTool, HttpRequestTool, Langchain.agent and 3 more. With Runwork, you don't need to learn n8n's workflow syntax—just describe what you want in plain English.

StickyNote RssFeedReadTool HttpRequestTool Langchain.agent Langchain.chatTrigger Langchain.memoryBufferWindow Langchain.lmChatGoogleGemini

Based on n8n community workflow. View original

Ready to build this?

Start with this recipe and customize it to your needs.

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