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๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration

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๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration ใซใคใ„ใฆ

GHL MCP server to GHL Demo Sub Account

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{
  "mcpServers": {
    "MCP-GHL": {
      "command": "python",
      "args": [
        "scripts/start_server.py"
      ]
    }
  }
}

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What is ๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration?

This server exposes GoHighLevel (GHL) sub-account tools to an Anthropic-powered LangGraph agent using the Model Context Protocol (MCP). It acts as a secure intermediary between the LangChain ecosystem and GHL APIs, designed for clean modular separation and zero-handoff latency.

How to use ๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration?

Create a .env file with your GHL API key, sub-account ID, and base URL. Install dependencies with pip install -r requirements.txt. Start the server using uvicorn mcp_server:app --host 0.0.0.0 --port 8000 or the startup script. Test connection with python examples/simple_client.py or run interactive mode.

Key features of ๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration

  • FastAPI MCP server exposing GHL sub-account tools
  • Dynamic tool registration via LangChain MCP adapters
  • Secure credential loading through .env variables
  • Pre-built tools for contacts, pipelines, and automations
  • Supports Claude-based LangGraph Agents as MCP clients
  • Zero-coupling between agent and GHL API

Use cases of ๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration

  • A Claude-powered agent retrieves contact details from GHL in real time
  • Automates pipeline and opportunity updates without manual login
  • Triggers custom workflows by calling webhook endpoints
  • Creates notes on contacts based on user conversation context
  • Enables LangGraph agents to manage GHL sub-accounts programmatically

FAQ from ๐Ÿง  GHL MCP Server โ€“ Anthropic LangGraph Agent Integration

What is the purpose of this server?

It acts as a secure intermediary between LangChain agents and GoHighLevel APIs, exposing GHL tools (contacts, pipelines, automations) to Claude-based LangGraph agents via MCP.

What environment variables are required?

You need GHL_API_BASE_URL, GHL_API_KEY, GHL_SUB_ACCOUNT_ID, and optionally ALLOWED_ORIGINS. All are set in a .env file at the root of ghl_mcp_server/.

Where can I find the GHL credentials?

  • GHL_API_KEY: GHL Settings โ†’ API Keys
  • GHL_SUB_ACCOUNT_ID: URL bar while inside the sub-account dashboard
  • Webhook/Funnel/Contact IDs: found in respective page URLs or contact details

What are the runtime dependencies?

Python 3.11+, FastAPI, and the langchain-mcp-adapters package. Optionally NGROK or Azure App Service for public MCP endpoint exposure.

How do tools communicate with the agent?

All tool usage is routed over HTTP via LangChainโ€™s MCP standard. The server exposes endpoints that the MCP client calls using MCPClient.load_tools(). No data leaves the userโ€™s GHL sub-account except through authorized API calls.

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