How to Use the GoHighLevel Alternative MCP in Google ADK

Run deep, long-context audits on your GHL contacts and opportunities using the Google ADK.

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Connect GoHighLevel Alternative MCP to Google ADK

Create your Vinkius account to connect GoHighLevel Alternative to Google ADK 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 Alternative with Google ADK

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Audit contacts with Google ADK

The `audit_contacts` tool retrieves your customer profiles so Gemini models can analyze them for formatting errors and communication gaps. It handles thousands of records at once using the framework's massive context window. By feeding contact histories directly to the Google ADK, your agent spots patterns in customer churn. It links your GHL marketing data directly to your enterprise analytics.

Analyze pipeline opportunities via this MCP Server

The `audit_opportunities` tool extracts deal stages and values from your sales pipeline for immediate evaluation. It lets your agent cross-reference pipeline health with external data stored in BigQuery. Running this MCP Server tool inside the Google ADK gives you a clear picture of sales velocity. The agent runs statistical models on your deal flow without requiring separate integrations.

Automate task audits across your team

The `audit_tasks` tool identifies incomplete assignments and neglected leads within your sales workspace. It exposes operational bottlenecks by checking task completion times. Your Google ADK agent parses these tasks to suggest better resource allocation. It matches open tasks against team availability to keep your sales reps focused on the highest-value opportunities.

Setup guide

Set up GoHighLevel Alternative MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with GoHighLevel Alternative tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="GoHighLevel Alternative_agent",
    model="gemini-2.0-flash",
    instruction="You have access to GoHighLevel Alternative tools via MCP.",
    tools=mcp_tools,
)

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Common questions about GoHighLevel Alternative MCP in Google ADK

You instantiate McpToolset with the server URL and pass it to your LlmAgent in Python. The Google ADK automatically maps the GHL audit tools for Gemini models using the MCP standard.

Yes. Your Google ADK agent can fetch pipeline opportunities from the GHL server and join them with historical enterprise data in BigQuery.

Yes. You can feed entire contact lists and task histories into Gemini models via Google ADK to run deep, multi-million token evaluations.

Use the optional tool name filter when setting up your toolset. This restricts your agent to specific operations like task auditing while hiding opportunity data from the MCP interface.

All task details and contact records run through a zero-trust, sandboxed connection. Vinkius secures the credentials, ensuring your raw GHL data never leaks into public LLM training sets.

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