How to Use the Salesforce Marketing Cloud MCP in Google ADK

Q: How do I configure the Google ADK to use the Salesforce Marketing Cloud MCP Server?

Instantiate McpToolset using StreamableHttpServerParameters pointing to your Vinkius endpoint, and pass this toolset into your Google ADK LlmAgent constructor. This exposes the campaign tools directly to Gemini models.

Q: Can I restrict which Salesforce Marketing Cloud tools my Google ADK agent can use?

Yes, use the optional toolnames filter when setting up your McpToolset to expose only what you need. For example, you can expose sfsearchcampaigns while blocking campaign creation tools to prevent accidental budget allocations.

Q: How does Gemini use Salesforce Marketing Cloud performance data alongside BigQuery?

Gemini reads the aggregate metrics from sfcampaignperformance and cross-references them with raw sales data in BigQuery. This allows the Google ADK agent to calculate deep ROI metrics without manual data exports.

Q: Can the Google ADK agent track who has responded to a campaign?

Yes, the Google ADK agent calls sfcampaignmembers to get a list of enrolled leads and contacts. This tool returns their specific status, such as Responded or Registered, along with the exact date they interacted with your Salesforce Marketing Cloud campaign.

Run long-context Gemini agents with Google ADK to analyze Salesforce Marketing Cloud campaigns directly.

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Connect Salesforce Marketing Cloud MCP to Google ADK

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Setup Salesforce Marketing Cloud with Google ADK

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Analyze Performance with Google ADK

`sf_campaign_performance` pulls aggregate metrics including lead counts, conversions, and actual costs grouped by campaign type. Gemini's million-token context window in the Google ADK digests this entire Salesforce Marketing Cloud performance dataset to find patterns that standard analytics tools miss. The Google ADK agent joins this Salesforce Marketing Cloud data with your BigQuery datasets to map offline revenue back to specific campaigns. By executing `sf_campaigns_by_status`, the agent isolates active initiatives and builds real-time performance reports inside Google Cloud.

Ground Gemini Decisions in Live CRM Data

`sf_search_campaigns` searches your Salesforce Marketing Cloud database by name to pull down status, type, budget, and conversion metrics. This tool grounds the Gemini model in Google ADK, stopping hallucinated campaign details before they enter your enterprise workflows. When the Google ADK model identifies a gap in your marketing mix, it runs `sf_create_campaign` to establish a new tracking container. The model sets the planned budget and dates, returning the new Salesforce Marketing Cloud ID directly to your Google ADK pipeline.

Manage Campaign Members via MCP Server

`sf_add_campaign_member` enrolls leads or contacts into target Salesforce Marketing Cloud campaigns to track their conversion path. Your Google ADK agent runs this tool after analyzing customer intent data pulled from Vertex AI. The Google ADK agent verifies current enrollment lists using `sf_campaign_members` to prevent double-contacting. This tool returns Salesforce Marketing Cloud member names, types, and response dates, giving your ADK agent the full history needed to personalize follow-up tasks.

Setup guide

Set up Salesforce Marketing Cloud 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 Salesforce Marketing Cloud 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="Salesforce Marketing Cloud_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Salesforce Marketing Cloud tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Salesforce Marketing Cloud MCP in Google ADK

Instantiate `McpToolset` using `StreamableHttpServerParameters` pointing to your Vinkius endpoint, and pass this toolset into your Google ADK `LlmAgent` constructor. This exposes the campaign tools directly to Gemini models.

Yes, use the optional `tool_names` filter when setting up your `McpToolset` to expose only what you need. For example, you can expose `sf_search_campaigns` while blocking campaign creation tools to prevent accidental budget allocations.

Gemini reads the aggregate metrics from `sf_campaign_performance` and cross-references them with raw sales data in BigQuery. This allows the Google ADK agent to calculate deep ROI metrics without manual data exports.

Yes, the Google ADK agent calls `sf_campaign_members` to get a list of enrolled leads and contacts. This tool returns their specific status, such as Responded or Registered, along with the exact date they interacted with your Salesforce Marketing Cloud campaign.

The MCP server only accesses campaign metadata, member statuses, and lead/contact identifiers. It runs inside a zero-trust V8 sandbox on Vinkius, meaning your credentials are never exposed to the Google ADK execution environment or stored on disk.

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