How to Use the Mailshake MCP in AutoGen

Q: How do I load the Mailshake MCP Server into AutoGen?

Install autogen-extmcp and use mcpservertools with the Streamable HTTP parameters. The framework automatically converts the tool schemas using McpToolAdapter for your AssistantAgent.

Q: How do AutoGen agents handle Mailshake API errors?

If listcampaignrecipients returns an error, the executing agent reads the failure message and proposes a fix to the group. The agents discuss the error and retry with corrected parameters.

Deploy competing AutoGen agents to debate and manage your Mailshake campaigns through a unified MCP Server connection.

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Connect Mailshake MCP to AutoGen

Create your Vinkius account to connect Mailshake 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 Mailshake with AutoGen

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Perplexity

Debate Campaign Pauses

The `pause_outreach_campaign` tool sits at the center of agent negotiations. A performance-monitoring agent watches bounce rates, while a sales-quota agent argues to keep the campaign running. They debate the metrics pulled from `get_campaign_details`. Only when they reach a consensus does the system actually execute the pause command. You build safeguards directly into the conversation logic.

Cross-Examine Mailshake MCP Server Leads

The `list_campaign_leads` tool feeds raw prospect data to your qualification agents. One agent reads the lead profile, while another challenges its fit based on your ideal customer profile. If the lead passes the debate, a third agent executes `add_prospects_to_campaign` to push them into a new sequence. You get a fully automated, peer-reviewed pipeline that rejects weak targets before they receive an email.

Audit Message Content Automatically

The `get_message_content` and `list_outreach_messages` tools let your copywriter agents review outgoing text. They pull the active sequence drafts and critique the phrasing. A compliance agent verifies the copy against spam filter rules. It checks the history via `get_lead_history` to see if similar phrasing caused bounces previously, forcing the copywriter agent to revise the text.

Setup guide

Set up Mailshake 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 Mailshake 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="Mailshake_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Mailshake 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="Mailshake_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Mailshake 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 Mailshake. 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 Mailshake MCP in AutoGen

Install `autogen-ext[mcp]` and use `mcp_server_tools` with the Streamable HTTP parameters. The framework automatically converts the tool schemas using `McpToolAdapter` for your AssistantAgent.

Yes. You pass the tool list to any agent participating in the chat. A researcher agent can call `list_outreach_campaigns` while a manager agent reviews the results.

If `list_campaign_recipients` returns an error, the executing agent reads the failure message and proposes a fix to the group. The agents discuss the error and retry with corrected parameters.

Only if you configure it for full autonomy. You can require a human-in-the-loop approval step before any agent is allowed to trigger the `add_prospects_to_campaign` tool.

The underlying MCP connection operates on an ephemeral sandbox. Your recipient lists and campaign metrics are exposed only to the specific agents you authorize in your local runtime. Vinkius routes the authenticated request but never logs the payload.

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