How to Use the Actionstep MCP in AutoGen

Give your AutoGen agents access to Actionstep for consensus-driven case management.

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Connect Actionstep MCP to AutoGen

Create your Vinkius account to connect Actionstep 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 Actionstep with AutoGen

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Perplexity

Fuel AutoGen agent debates

Integrating your multi-agent setups with live firm data happens through the Actionstep MCP Server via `get_matter_details`. A compliance agent pulls the case file while a billing agent reviews the associated costs. They argue over discrepancies before presenting a final summary to the user. This friction produces highly accurate reviews of complex legal situations.

Delegate contact management

Assigning an administrative agent to handle `list_contacts` and `create_contact` removes manual data entry from your plate. The system detects missing parties in a contract draft and proposes adding them. Another agent verifies the formatting rules before the write operation executes. You get perfectly structured records without touching the keyboard.

Reconcile time and tasks

Fetching current workloads requires calling `list_time_entries` alongside `list_legal_tasks`. Your performance agent compares hours billed against tasks completed. If the numbers look wrong, the agents flag the specific matter for human review. The framework handles all the MCP schema conversions behind the scenes automatically.

Setup guide

Set up Actionstep 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 Actionstep 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="Actionstep_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Actionstep MCP in AutoGen

Install the autogen-ext package with MCP support. Pass your Vinkius HTTP URL into StreamableHttpServerParams to generate the tool list.

You assign specific capabilities to different agents. One handles contact creation while another strictly reads time entries.

The framework handles that completely. Its adapter translates the server's requirements into native Python functions.

Scripts fail when edge cases appear. Multi-agent systems deliberate over strange billing entries and ask for clarification instead of crashing.

Nobody outside your authorized connection. Vinkius processes your legal tasks, time entries, and matter notes in a zero-trust, ephemeral sandbox that vanishes the millisecond the agent conversation terminates.

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