How to Use the Messaggio MCP in AutoGen
Let your AutoGen agents debate and coordinate bulk Messaggio campaigns with built-in validation and status tracking.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Messaggio MCP to AutoGen
Create your Vinkius account to connect Messaggio 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.
Multi-Agent Campaigns with MCP Server
This MCP Server gives your entire AutoGen group access to tools like `send_message` and `send_simple_sms` to coordinate multi-channel communications. You can build a system where a copywriter agent drafts notifications, a compliance agent checks them, and a sender agent dispatches them. By separating responsibilities, you prevent accidental or poorly formatted messages from going out. The agents must reach a consensus on the template variables and sender identity before the dispatch tool is actually executed.
Automated Sender Verification
This MCP Server exposes `list_project_senders` and `get_sender` to let your agents verify active channels before sending. Running these validation checks helps your workflow verify that your custom sender IDs are fully registered and ready. If a specific WhatsApp sender is offline, the performance agent can suggest switching to an SMS sender. This negotiation happens entirely in the background, ensuring your notifications always find a working path.
Consensus-Based Bulk Dispatching
This MCP Server provides the `send_bulk` tool to let your agents review a target list, verify template matching, and trigger mass notifications safely. Your agents can cross-reference recipient lists with active layouts using `list_templates` before executing the batch. Once the campaign is running, a monitoring agent can repeatedly call `get_message_status` to track delivery rates. If the failure rate crosses a threshold, the safety agent can halt the campaign automatically.
Set up Messaggio 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 Messaggio 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="Messaggio_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Messaggio 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="Messaggio_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Messaggio 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 Messaggio. 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 Messaggio MCP in AutoGen
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