How to Use the Missive MCP in AutoGen

Q: How do I register Missive MCP Server tools with an AutoGen agent?

Use mcpservertools with StreamableHttpServerParams pointing to your Vinkius Missive endpoint. Pass the resulting tool list directly into your AutoGen AssistantAgent constructor.

Q: Can AutoGen agents collaborate on a single Missive email?

Yes, they can. One agent can use createdraft to generate the initial email, while another agent inspects the conversation history with getconversation to review and refine the text before sending.

Deploy AutoGen agents to debate, review, and collaborate on Missive drafts and customer conversations before sending.

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Connect Missive MCP to AutoGen

Create your Vinkius account to connect Missive 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.

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Setup Missive with AutoGen

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Multi-Agent Inbox Triage and Debate

`list_conversations` fetches new threads so your AutoGen agents can debate how to handle incoming mail. A security agent reviews the message details via `list_messages` to check for spam or phishing before any action is taken. They debate the risk level inside your AutoGen workflow. Once they reach a consensus, a triage agent uses `create_post` to assign the thread or apply a label based on their joint decision.

Consensus-Driven Draft Review with AutoGen MCP Server

`create_draft` allows a writer agent to generate a response while a separate reviewer agent checks it against contact info. The reviewer agent inspects the conversation history with `get_conversation` to review and refine the text before sending. If the reviewer agent finds an issue, it asks the writer agent to update the draft. They pass the draft back and forth until they agree, and only then does the sender agent call `send_draft` to deliver it.

Collaborative Team Updates via Multi-Agent Workflows

`get_me` verifies the agent's user identity and permissions before it interacts with team threads. This keeps your internal discussions clean with coordinated agent updates. The agents can then collaborate on complex tasks, using `create_post` to leave internal comments explaining their decisions. This gives your human team clear visibility into the agents' debate and final consensus.

Setup guide

Set up Missive 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 includes mcp_server_tools for 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 AssistantAgent and call agent.run(). The agent invokes Missive tools and returns structured results.

agent.py

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="Missive_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Missive data")
print(result.messages[-1].content)

Get your connection token →

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. McpWorkbench is 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=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

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="Missive_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Missive data")
    print(result.messages[-1].content)

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 Missive. 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 Missive MCP in AutoGen

Use mcp_server_tools with StreamableHttpServerParams pointing to your Vinkius Missive endpoint. Pass the resulting tool list directly into your AutoGen AssistantAgent constructor.

Yes, they can. One agent can use create_draft to generate the initial email, while another agent inspects the conversation history with get_conversation to review and refine the text before sending.

The framework uses conversational debate. If one agent wants to call send_draft but another flags a security risk in list_contacts, they negotiate in the chat log until they reach a consensus.

Yes, the AutoGen MCP adapter supports both. When hosting on Vinkius, you will use the Streamable HTTP transport to securely connect your multi-agent system to the Missive API.

Your token is stored as an encrypted environment variable on Vinkius. It is injected only at runtime inside an isolated V8 sandbox, ensuring your email drafts and contact databases remain completely private.

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