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GHL MCP Server – Anthropic LangGraph Agent Integration

@JewelreyBoxAI

Repository

Basic information

Category

AI & Agents

Transports

stdio

Author

JewelreyBoxAI

About GHL MCP Server – Anthropic LangGraph Agent Integration

GHL MCP server to GHL Demo Sub Account

#mathgpt#math-solver#math-assistant

GHL MCP Server – Anthropic LangGraph Agent Integration config

Add this server to your MCP-compatible client using the configuration below.

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

GHL MCP Server – Anthropic LangGraph Agent Integration tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is 🧠 GHL MCP Server – 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 🧠 GHL MCP Server – 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 🧠 GHL MCP Server – 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 🧠 GHL MCP Server – 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

Frequently asked questions

1

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.

2

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/`.

3

Where can I find the GHL credentials?

- `GHL_API_KEY`: GHL Settings → 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

4

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.

5

How do tools communicate with the agent?

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

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