How to Use the Collect MCP in AutoGen

Q: Can AutoGen agents review my Collect history?

Yes, agents use listrequests to debate the history of a project. They can then identify patterns that a single agent might miss.

Q: Will AutoGen agents negotiate Collect message content?

Agents can use sendmessage once they agree on the draft. They use the tool output to verify the message was sent correctly.

Enable debate-driven data management by connecting Collect to AutoGen agents.

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Connect Collect MCP to AutoGen

Create your Vinkius account to connect Collect 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 Collect with AutoGen

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Perplexity

Debating requests with AutoGen

Let your security agent check `create_request` parameters while your project agent evaluates the recipient list. They debate the validity of each request before execution. This prevents errors before they happen. Your agents reach a consensus that balances risk and performance.

Monitoring campaigns via an MCP Server

Assign an agent to call `list_campaigns` and report the findings to the group. If the data looks off, the agents challenge the current status. This turns your monitoring into a conversation. You get a decision-backed summary instead of raw logs.

Handling feedback with AutoGen

Use `send_message` as a tool for your agents to resolve disputes with recipients. Your agents negotiate the content of the message based on previous `get_request` data. This ensures every message is reviewed. Your team saves time by automating the back-and-forth.

Setup guide

Set up Collect 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 Collect 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="Collect_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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

Get your connection token →

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Common questions about Collect MCP in AutoGen

You pass the Collect tool list to your AssistantAgent constructor. This allows your agents to call the API as part of their collaborative problem-solving process.

Yes, agents use `list_requests` to debate the history of a project. They can then identify patterns that a single agent might miss.

Agents can use `send_message` once they agree on the draft. They use the tool output to verify the message was sent correctly.

The agents recognize the error output and discuss a retry strategy. They don't just fail; they adjust their approach based on the feedback.

Yes, we use a zero-trust architecture where only authorized agents receive tool outputs. All communication is scoped to your specific endpoint token.

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