How to Use the Clinical Reasoning Prover MCP in AutoGen

Force consensus on diagnosis. Use Clinical Reasoning Prover with AutoGen to let agents debate and validate treatment plans.

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Connect Clinical Reasoning Prover MCP to AutoGen

Create your Vinkius account to connect Clinical Reasoning Prover 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 Clinical Reasoning Prover with AutoGen

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Debate clinical logic in AutoGen

Configure your AutoGen agents to use `validate_clinical_reasoning` as a final check before finalizing a plan. If the agent's logic fails the VINDICATE review, the system forces a re-evaluation before the agents can reach consensus. Your agents act as a medical board. One agent proposes a treatment, while another uses this tool to challenge the reasoning. They negotiate until the plan meets all AHA and ACC criteria.

Automate multi-agent safety checks

The tool acts as an objective arbiter for your AutoGen team. It checks for contraindications and pharmacokinetics, flagging risks that a single agent might overlook during a heated debate. You build systems where safety is non-negotiable. If the tool detects a missing evidence level or a potential drug interaction, it provides the feedback needed to force a correction.

Integrate MCP into agent conversations

AutoGen handles the schema conversion for you, turning this MCP Server into a native agent tool. Your team of assistants can call it mid-discussion to verify the triage severity of a patient. This setup creates a robust verification loop. The agents don't just guess; they use the server to pressure-test their assumptions against real clinical guidelines.

Setup guide

Set up Clinical Reasoning Prover 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 Clinical Reasoning Prover 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="Clinical Reasoning Prover_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Clinical Reasoning Prover 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="Clinical Reasoning Prover_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Clinical Reasoning Prover 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 Clinical Reasoning Prover. 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 Clinical Reasoning Prover MCP in AutoGen

The agents share the tool output as part of their conversation history. If the reasoning fails validation, the agents see the error and adjust their proposals accordingly.

Yes, you pass the tools to the AssistantAgent. All agents in the group chat can then trigger the validation tool when they need to ground their arguments.

It serves as the ground truth. When agents debate a diagnosis, they call this tool to check the guidelines, effectively ending the dispute with objective data.

The server manages the tool calls independently for each agent. You can run concurrent validations as the agents work through a case.

The server uses a zero-trust, ephemeral architecture. Patient identifiers are processed locally within the agents' conversation thread, with no persistent storage on the Vinkius side.

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