How to Use the Cordial MCP in CrewAI

Q: How do I limit Cordial tool access in CrewAI?

You use the toolfilter parameter when setting up your agents. This ensures specific agents only see the tools they need to perform their role.

Deploy a crew of autonomous agents to monitor Cordial campaigns and manage subscriber data without human input.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Cordial MCP to CrewAI

Create your Vinkius account to connect Cordial 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.

GDPR Free for Subscribers

Setup Cordial with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Autonomous subscriber operations

Assign a dedicated agent to clean up your subscriber lists using `list_contacts`. It identifies inactive users and updates their status via `upsert_subscriber`. The crew works in sequence, meaning one agent prepares the data while another performs the update. It keeps your database clean while you focus on strategy.

Cross-boundary campaign analysis

Deploy a research agent to fetch campaign data with `list_marketing_campaigns`. It shares this info with an analyst agent that evaluates performance metrics. By using `search_campaigns_by_name`, the crew locates relevant assets across the platform boundary. It turns raw performance data into actionable reports automatically.

System-level configuration management

Use the `get_account_details` tool to let your agents verify platform settings before launching a new blast. It prevents configuration errors that usually require a human check. Agents also review message definitions with `list_messages` to ensure templates match current requirements. It acts as an automated quality control layer for your messaging stack.

Setup guide

Set up Cordial MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. 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 Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Cordial tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Cordial Analyst",
    goal="Access and analyze Cordial data via MCP.",
    backstory="Expert analyst with direct Cordial access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Cordial transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

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="Cordial Analyst",
        goal="Access and analyze Cordial data via MCP.",
        backstory="Expert analyst with direct Cordial access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Cordial transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 Cordial. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Cordial now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Cordial MCP in CrewAI

Absolutely, individual agents share memory and can pass results from one tool call to another. One agent can list subscribers while the next updates their attributes.

You use the tool_filter parameter when setting up your agents. This ensures specific agents only see the tools they need to perform their role.

The MCP Server is designed to handle multiple concurrent requests. You can run your entire crew against the same endpoint without hitting rate limits.

SSE or Streamable HTTP works best for long-running agent tasks. These transports keep the connection stable while your agents collaborate.

We utilize a zero-trust model where every tool call requires an authenticated token. All subscriber records are processed in memory and deleted immediately after the agent finishes its work.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript