How to Use the Mailchimp MCP in CrewAI
Deploy multi-agent marketing teams in CrewAI using this MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Mailchimp MCP to CrewAI
Create your Vinkius account to connect Mailchimp to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Analyze Mailchimp stats with CrewAI
`get_audience` and `list_audiences` feed raw list statistics directly from the MCP Server to your research agents. A dedicated analyst persona can pull member counts, open rates, and click metrics across all your lists. They digest the numbers and pass a summary to the rest of the crew. Your team doesn't need to guess which segments are active. By running `list_members`, the analyst can extract specific email addresses and tags. This shared memory allows the next agent to target the right people automatically.
Draft emails with specialized agents
`create_campaign` gives your copywriter agent the ability to build actual marketing assets. Once the researcher identifies a target audience, the copywriter drafts the subject line and body copy. The MCP Server executes the creation and returns a campaign ID. A separate manager agent can then use `get_campaign` to review the draft. This hierarchical setup ensures that the content meets your formatting standards before it ever hits the outbox.
Control live sends with moderator agents
`send_campaign` is a high-risk operation that triggers an immediate email blast. You can assign this specific tool exclusively to a senior moderator agent. The rest of the crew handles the drafting, but only the moderator holds the keys to the actual send. After the blast goes out, a reporting agent takes over. They call `get_report` to monitor the open rates and click performance. The team adjusts their strategy for the next run based on hard data.
Set up Mailchimp MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically. - 3
Kick off your crew
Create a
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Mailchimp tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Mailchimp Analyst",
goal="Access and analyze Mailchimp data via MCP.",
backstory="Expert analyst with direct Mailchimp access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Mailchimp transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters
server_params = SseServerParameters(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
with MCPServerAdapter(server_params) as mcp_tools:
agent = Agent(
role="Mailchimp Analyst",
goal="Access and analyze Mailchimp data via MCP.",
backstory="Expert analyst with direct Mailchimp access.",
tools=mcp_tools,
)
task = Task(
description="List recent Mailchimp transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mailchimp. 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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60%
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Common questions about Mailchimp MCP in CrewAI
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