How to Use the CM.com MCP in AutoGen
Deploy multi-agent debates in AutoGen to validate, approve, and send CM.com messages.
Works with every AI agent you already use
…and any MCP-compatible client
Connect CM.com MCP to AutoGen
Create your Vinkius account to connect CM.com 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.
Consensus-driven dispatch with AutoGen
The `send_sms` tool transmits text alerts, and `send_whatsapp` sends rich templates. In AutoGen, a copywriter agent drafts the message while a compliance agent reviews it before hitting the CM.com API. Only after both agents reach consensus does the execution agent trigger the messaging tool. This multi-agent debate prevents formatting errors and compliance violations. You define the negotiation rules, ensuring no message goes out without passing through your automated editorial board first.
Secure OTP delivery via this MCP Server
The `send_otp_sms` tool generates and sends verification codes, while `verify_otp` handles the validation. An AutoGen security agent can monitor this process, deciding when to escalate a failed CM.com SMS attempt to voice OTP based on real-time conversation logs. The agents debate the security risk of the transaction. If the risk score is high, they require voice verification instead of SMS, coordinating the API calls dynamically.
AutoGen budget guardrails for CM.com
The `get_balance` tool checks your current account funds, and `send_bulk_sms` handles high-volume campaigns. An AutoGen budget-monitoring agent runs `get_balance` to protect your CM.com account from running dry before allowing the marketing agent to trigger bulk sends. If the cost of the bulk campaign exceeds the available balance, the budget agent blocks the execution. The agents then negotiate a smaller recipient list or alert a human supervisor for top-ups.
Set up CM.com 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 CM.com 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="CM.com_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent CM.com 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="CM.com_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent CM.com 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 CM.com. 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 CM.com MCP in AutoGen
Use it with your favorite AI tools
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