AI Agent to chat with you Search Console Data, using OpenAI and Postgres

AI Agent for Search Console enables seamless interaction with your Search Console data through a chat interface. Users can easily request insights, retrieve property lists, and generate custom reports by simply conversing with the AI. This workflow automates data retrieval, ensuring accurate and timely responses while enhancing user experience with natural language processing.

7/8/2025
30 nodes
Complex
webhookcomplexlangchainsticky noterespondtowebhookexecuteworkflowtriggeraggregateadvanceddatabasedataintegrationapilogicrouting
Categories:
Complex WorkflowWebhook TriggeredBusiness Process Automation
Integrations:
LangChainSticky NoteRespondToWebhookExecuteWorkflowTriggerAggregate

Target Audience

  • Digital Marketers: Professionals looking to analyze their website performance through Google Search Console data.
    - SEO Specialists: Experts who need to extract insights for optimization and strategy planning.
    - Business Owners: Individuals wanting to understand their website's visibility and performance metrics.
    - Data Analysts: Analysts seeking to automate data retrieval and reporting processes related to Search Console metrics.
    - Developers: Technical users interested in integrating Search Console data into their applications or dashboards.

    • Problem Solved

    This workflow addresses the need for efficient data retrieval from Google Search Console, allowing users to interact with their data through a chat interface. It simplifies the process of querying Search Console properties, fetching insights, and presenting them in a user-friendly manner, eliminating the need for manual API calls and technical knowledge.

    Workflow Steps

  • Webhook Trigger: The workflow starts by receiving a POST request containing chatInput and sessionId from users.
    2. Set Fields: The incoming data is processed to assign values to chatInput, sessionId, and the current date (date_message).
    3. AI Agent Interaction: The AI Agent uses the OpenAI Chat Model to interpret user requests and interact naturally, confirming their data needs.
    4. Tool Calls: Depending on the user’s request type (either website_list or custom_insights), the appropriate tool is invoked to fetch data from the Search Console.
    5. API Requests: The workflow constructs and sends API requests to the Google Search Console, retrieving either the list of properties or custom insights based on the user's input.
    6. Data Processing: The response from the API is processed to create structured arrays for easy handling.
    7. Aggregation: The results are aggregated and formatted into a response that is sent back to the user, ensuring clarity and usability.
    8. Response to Webhook: Finally, the workflow sends the aggregated data back to the user through the webhook, completing the interaction.

    • Customization Guide

    To customize this workflow:
    - Modify the AI Agent's System Prompt: Adjust the instructions given to the AI agent to change how it interacts with users.
    - Change API Endpoints: Update the endpoints in the HTTP request nodes to point to different Google API services if needed.
    - Adjust Data Processing Logic: Modify the logic in the Set fields or Aggregate nodes to fit specific data structures or requirements.
    - Enhance Security: Change authentication methods in the webhook and API calls to meet your security standards.
    - Expand Data Retrieval: Add additional fields or parameters in the API requests to gather more detailed insights from Search Console.