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Automated Facebook comment management with GPT-4o and LangChain

Amanda BenksAmanda Benks
1708 views
2/3/2026
Order ProcessingGoogle SheetsShopifyE-commerceData Sync
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🤖 Facebook AI Agent with MCP Server – Built for Smart Engagement and Automation

Hi! I’m Amanda 🥰😘 — I build intelligent automations with n8n and Make.

This powerful workflow was designed to help teams automatically handle Facebook page interactions with AI. Using Meta Graph API, LangChain, MCP Server, and GPT-4o, it allows your AI agent to search for posts, read captions, fetch comments, and even reply or message followers, all through structured tools.

🔧 What the workflow does

  • Searches for recent media using Facebook Page ID and access token
  • Reads and extracts captions or media URLs
  • Fetches comments and specific replies from each post
  • Replies to comments automatically with GPT-generated responses
  • Sends direct messages to followers who commented
  • Maps user input and session to keep memory context via LangChain
  • Communicates via Server-Sent Events (SSE) using your MCP Server URL

🧰 Nodes & Tech Used

  • LangChain Agent + Chat Model with GPT-4o
  • Memory Buffer for session memory
  • toolHttpRequest to search media, comments, and send replies
  • MCP Trigger and MCP Tool (custom SSE connection)
  • Set node for input and variable assignment
  • Webhook and JSON for Facebook API structure

⚙️ Setup Instructions

  1. Create your Facebook App in Meta Developer Portal
  2. Add your Facebook Page ID and Access Token in the Set node
  3. Update the MCP Server Tool URL in the MCP Facebook node
    • Use your n8n server URL (e.g. https://yourdomain.com/mcp/server/facebook/sse)
  4. Trigger the workflow using the included LangChain Chat Trigger
  5. Interact via text to ask the agent to:
    • “Get latest posts”
    • “Reply to comment X with this message”
    • “Send DM to this user about...”

👥 Who this is for

  • Social media teams managing multiple Facebook pages
  • Brands automating engagement with followers
  • Agencies creating smart, autonomous digital assistants
  • Developers building conversational bots for Facebook

✅ Requirements

  • Meta Graph API access
  • Facebook Page (with permissions)
  • n8n instance (Cloud or Self-hosted)
  • MCP Server configured (SSE Endpoint enabled)
  • OpenAI API Key (for GPT-4o + LangChain)

🌐 Want to use this workflow?

❤️ Buy workflows: https://iloveflows.com
☁️ Try n8n Cloud: https://n8n.partnerlinks.io/amanda

n8n LangChain AI Agent Workflow

This n8n workflow demonstrates the core components of building an AI agent using LangChain nodes within n8n. It provides a foundational structure for creating conversational AI agents that can interact, remember context, and potentially use external tools.

What it does

This workflow sets up a basic LangChain AI agent environment within n8n. Specifically, it includes:

  1. Triggers on chat messages: It is designed to start when a chat message is received, indicating an interaction with an AI agent.
  2. Initializes an AI Agent: It sets up an AI Agent node, which is the orchestrator for the conversational flow.
  3. Configures a Chat Model: It integrates an OpenAI Chat Model (likely gpt-4o as hinted by the directory name, though the JSON only specifies OpenAI Chat Model) to power the agent's language understanding and generation capabilities.
  4. Adds Simple Memory: It includes a "Simple Memory" node to allow the AI agent to retain context from previous interactions within a conversation.
  5. Includes AI Tools (HTTP Request & MCP Client): It demonstrates the inclusion of two AI tools that the agent could potentially use:
    • An HTTP Request Tool for making web requests.
    • An MCP Client Tool (Model Context Protocol Client) for interacting with other Model Context Protocol services.
  6. Includes an MCP Server Trigger: This suggests the workflow might also act as a server for other MCP clients to interact with.
  7. Data Transformation: A "Set" node is included, which can be used to edit or transform data at various points in the workflow.
  8. Documentation: A "Sticky Note" node is present for adding comments or documentation directly within the workflow.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • OpenAI API Key: Configured as an n8n credential for the "OpenAI Chat Model" node.
  • LangChain Nodes: Ensure the @n8n/n8n-nodes-langchain package is installed and enabled in your n8n instance.
  • Model Context Protocol (MCP): If you intend to use the MCP Client/Server tools, you'll need an understanding of MCP and potentially other MCP-compatible services.

Setup/Usage

  1. Import the workflow: Download the JSON content and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key as a credential in n8n and link it to the "OpenAI Chat Model" node.
  3. Customize AI Agent:
    • Open the "AI Agent" node and configure its prompt, tools, and other settings according to your specific use case.
    • Define how the agent should use the "HTTP Request Tool" and "MCP Client Tool" by configuring their respective settings within the "AI Agent" node.
  4. Activate the Workflow: Once configured, activate the workflow to start listening for chat messages.
  5. Test: Send a chat message to the configured "Chat Trigger" to test the AI agent's response.

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