How to Use the Dastra MCP in AutoGen

Debate privacy policy with AutoGen. Let agents negotiate Dastra compliance tasks using multi-agent deliberation.

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Connect Dastra MCP to AutoGen

Create your Vinkius account to connect Dastra 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 Dastra with AutoGen

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Debate Dastra actions in AutoGen

Deploy a team of agents that discuss how to handle incoming DSRs. One agent calls `list_dsr` to fetch the queue while another evaluates the urgency of each request. They reach a consensus on which requests need immediate attention. You get a deliberated plan instead of a single, unverified response.

Negotiate breach response with AutoGen

Have your security agent and legal agent analyze breach records retrieved via `list_breaches`. They challenge each other on reporting requirements based on the details in the records. This prevents rushed decisions. Your agents negotiate the correct path forward before you finalize any record in Dastra.

Coordinate workspace management in AutoGen

Use `list_workspaces` and `list_tags` to let your agents organize your compliance environment. They discuss the best way to categorize records based on your existing structure. This ensures your Dastra setup remains consistent. You don't have to monitor every move, as the agents reach an agreement before executing updates.

Setup guide

Set up Dastra 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 Dastra 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="Dastra_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Dastra MCP in AutoGen

Install the MCP extension for AutoGen. Use the streamable HTTP parameters to connect the server, then pass the tool list to your AssistantAgent.

They can. By giving multiple agents access to the same tools, they compare notes and challenge each other on the data they retrieve.

You can set the agents to require human approval for final record updates. They do the heavy lifting of debating the options first.

They pass the tool outputs through the conversation context. Every agent sees the results of the previous agent's call.

The server uses authenticated tokens for every request. Only your specific AutoGen agents gain access to the data records.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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