How to Use the Emarsys MCP in AutoGen
Deploy AutoGen agents to debate, audit, and optimize your Emarsys marketing campaigns and automation setups.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Emarsys MCP to AutoGen
Create your Vinkius account to connect Emarsys 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.
Debating Emarsys campaign setups with AutoGen
The `get_campaign_details` tool feeds raw campaign settings directly into AutoGen's multi-agent conversations, allowing a marketing agent and a compliance agent to debate the setup. One agent checks the targeting parameters while the other flags potential brand safety issues based on the campaign payload. This consensus-driven approach ensures no campaign goes live with incorrect settings. The agents negotiate changes using the actual JSON returned by `list_email_campaigns` to ensure complete alignment before execution.
Multi-agent audits using this MCP Server
The `quick_engagement_volume_audit` tool provides high-level volume metrics that AutoGen agents analyze from multiple perspectives. An analyst agent flags drop-offs in volume, while a strategy agent proposes adjustments to active contact lists. By using this MCP Server, your agents coordinate complex audits without manual data gathering. The agents call `list_marketing_contact_lists` and debate which audience segments require immediate attention based on recent volume trends.
Optimize Emarsys automation paths in AutoGen
The `list_automation_programs` tool exposes active workflow sequences to AutoGen's collaborative agent groups. A technical agent maps out the program steps, while a customer-experience agent analyzes whether the timing of the triggers makes sense. The agents use `list_trigger_events` to trace how external actions kick off automated journeys. They debate the efficiency of each trigger, ensuring your automation programs are tightly aligned with actual customer behaviors.
Set up Emarsys 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Emarsys tools and returns structured results.
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="Emarsys_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Emarsys data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Emarsys_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Emarsys data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Emarsys. 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.
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Common questions about Emarsys MCP in AutoGen
Use it with your favorite AI tools
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