Building a Meta & Keyword Targeting AI Agent with Langflow

Struggling to optimize your pages for the right keywords? Title tag optimization is a cornerstone of SEO, but it can be time-consuming and complex.

In this post, we'll show you how to build an AI-powered tool that streamlines keyword research and title tag optimization. This tool will help you identify the best keywords, analyze competitor pages, and generate optimized title tags and descriptions, all in one go.

This guide is based on a detailed video tutorial (seen below) where we build this agent step-by-step using Langflow, the Firecrawl API, the Serper API, and fine-tuned AI prompts.

This AI agent automates the process of keyword research and title tag optimization. It takes a target page URL and a target topic and generates the following output (as shown in the video at [0:33]):

• Target Page: The URL of the page you want to optimize.
• Keyword Targets: A list of relevant keywords for the page.
• Search Volume: The search volume for each keyword target.
• Optimized Title Tag: A keyword-optimized title tag.
• Optimized Description: A keyword-optimized meta description.
• Reasoning: An explanation of the title and description optimization.
• Competitors: A list of competitor pages used for keyword research.

How It Works at a High-Level

The core of this agent is a series of interconnected components that work together to analyze content and suggest relevant keywords and metadata. Here's a breakdown of the workflow:

• Input: You provide the target page URL and a target topic.
• Content Scraping: The agent uses the Firecrawl API to scrape the main content of the target page.
• SERP Analysis: The agent uses the Serper API to get search results for the target topic, identifying competitor pages.
• Keyword Extraction: The agent uses the Data for SEO API to extract keyword targets from the competitor pages.
• Optimization: The AI analyzes the scraped content, search results, and keyword targets to generate an optimized title tag and description.

Key Components and Tools

We'll be using the following tools and components:

• Langflow: A visual platform for building AI workflows. We're using the Datastax version, which is currently free (as discussed in the video at [2:55]).
• Firecrawl Scrape API: To scrape the content of web pages.
• Serper API: To get Google search results.
• Data for SEO API: To extract keyword data from competitor pages.
• OpenAI API: To power the AI agents.
• Custom Prompts: Carefully crafted instructions for the AI to perform each task.

What You'll Need

You can build and use this tool at a very low cost. Here’s what you’ll need:

1. OpenAI API Key: Get Started
2. Firecrawl API Key: Sign Up (Includes 500 free credits)
3. Serper API Key: Sign Up (Includes 2,500 free queries)
4. DataForSEO API Key: Sign Up (Includes free trial)

Quick Start Options

Before diving into the build process, here are a couple of quick ways to get started (as mentioned in the video at [3:35]):

• Download the Ready-Made Flow: If you want to skip the build process, you can download the complete Langflow workflow file and import it directly. You'll just need to add your API keys.
  • Download the Flow File from Github

• Try the Tool Online: Test the tool directly in your browser. Use the SEO Workflows interface to use the tool directly (as shown in the video at [4:22]).

  • Try the Online Tool on SEO Workflows

  *While the SEO Workflows tools charge small fees. Every user will be provided with free tokens to test the tools!

Building the Workflow Step-by-Step

If you're ready to build your own, here's a breakdown of the steps:

• Layout: Start by adding the core components to your Langflow canvas: Chat Input, Chat Output, Prompts, Agents, the Firecrawl Scrape API, and the Serper API (as seen in the video at [5:50]).
• Configure the Firecrawl API Tool: Add the custom code (provided in the GitHub link below) to enable the Firecrawl API as a tool within Langflow (as shown in the video at [6:55]).
  • Firecrawl Scrape Api Tool Code
• Create Prompts: Develop prompts for the Firecrawl API, the Serper API, and the Data for SEO API (as discussed in the video at [10:00]).
  • Scrape Main Content (FireCrawl API) Prompt
  • Serper API Prompt
  • Data for SEO Prompt
• Create Custom Component: Create a custom component for the Data for SEO API (as discussed in the video at [16:00]).
  • Data for SEO Custom Component Code
• Create Optimization Prompts: Develop a system prompt and an input prompt for the final optimization step (as discussed in the video at [21:20]).
  • Optimization Table Prompt
• Connect to Output: Connect the final components to the Chat Output node to complete the workflow.

Testing and Running the Workflow

• Input URLs: Provide your target page URL and target topic in the Chat Input node.
• Add API Keys: Enter your OpenAI, Firecrawl, Serper, and Data for SEO API keys (as mentioned in the video at [11:50]).
• Choose a Model: Select your preferred OpenAI model (e.g., gpt-4, gpt-4o, or gpt-3.5-turbo).
• Run the Flow: Execute the workflow and review the output, which will include optimized title tags, descriptions, and H1 tags (as shown in the video at [24:30]).

Conclusion

This AI-powered keyword research and title tag optimization agent can significantly streamline your SEO efforts. By automating the process of identifying relevant keywords and generating optimized metadata, you can save time and improve your website's search engine visibility.

Feel free to customize the prompts and components to fit your specific needs. Remember that the prompts used in the video are slightly different from the final, optimized prompts provided in the GitHub links provided.

Happy building, and happy optimizing!