How to Use the GoHighLevel MCP in AutoGen

Debate and execute GoHighLevel tasks with multi-agent AutoGen teams.

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Connect GoHighLevel MCP to AutoGen

Create your Vinkius account to connect GoHighLevel to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup GoHighLevel with AutoGen

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Negotiate CRM actions in AutoGen

Deploy a specialized agent to call `send_message` after a consensus check. Your team of agents discusses the lead's intent before firing off any outreach. This prevents automated spam. The agents verify the contact state first.

Manage pipelines with agent debate

Use `list_pipelines` to show your agents the current sales environment. They debate the best path forward for stagnant deals. One agent suggests a move while another critiques it. They settle on the best `list_opportunities` update.

Automate forms through agent consensus

Call `list_forms` to let your agents audit your lead capture setup. They check if the current configuration aligns with your team's goals. If something is off, they flag it for your review. It keeps your lead intake process clean.

Setup guide

Set up GoHighLevel MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes GoHighLevel tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="GoHighLevel_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent GoHighLevel data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="GoHighLevel_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent GoHighLevel data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GoHighLevel. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about GoHighLevel MCP in AutoGen

Yes, you pass the tool list to your agents, and they negotiate who uses what. It allows for complex, multi-step CRM operations.

Agents can discuss the error output from the MCP server and decide on a fix. They don't just crash; they try to resolve the issue.

You only provide one endpoint token to the server. Your actual CRM credentials never touch the agent execution environment.

It does. The tool adapter handles schema conversion, so your agents see the CRM tools as standard functions.

All tool traffic is contained within our V8 sandbox. We ensure your contact and conversation data is cleared immediately after the agents finish their task.

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