How to Use the TrueReview MCP in AutoGen

Q: What happens when multiple tools run with AutoGen and TrueReview?

The agents use the output of one tool call (e.g., getcontact) as input for another agent's reasoning process, leading to a highly iterative and thorough result.

Q: Is creating new contacts reliable using TrueReview, AutoGen, and MCP Server?

Yes. The agent can call createcontact and validate the result immediately, ensuring the new record is properly established in the system before proceeding with other tasks.

Let agents negotiate review strategy with AutoGen; manage complex marketing campaigns using TrueReview's MCP Server.

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Connect TrueReview MCP to AutoGen

Create your Vinkius account to connect TrueReview 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 TrueReview with AutoGen

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Perplexity

Debating Contact Targeting

You can set up a security agent and an outreach agent. One fetches all contacts using `list_contacts`, while the other determines if those contacts are eligible for a review request based on internal rules. The agents debate the list, challenging who gets the final say on which users receive the request via `send_review_request`.

Multi-Agent Campaign Planning

A performance agent can check past results using `get_report_summary`, while a strategy agent uses `list_campaigns`. They negotiate which campaign was most effective and why. This consensus process ensures the chosen marketing path is backed by data from the TrueReview MCP Server.

Location Analysis and Action

One agent finds all available business locations using `list_locations`. A second agent then uses that list to check for associated contacts via `list_contacts`. The agents collaborate until they form a consensus on the best location to focus their review efforts.

Setup guide

Set up TrueReview 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 TrueReview 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="TrueReview_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TrueReview. 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 TrueReview MCP in AutoGen

AutoGen makes multiple AI agents talk to each other about your goal. They use the MCP Server tools, like `create_contact` or `get_report_summary`, and debate which steps need to happen in what order.

Yes. The framework is designed for decision-making that isn't obvious. Multiple agents can challenge assumptions about your campaign goals, leading to a more robust plan.

The agents use the output of one tool call (e.g., `get_contact`) as input for another agent's reasoning process, leading to a highly iterative and thorough result.

The server handles customer contact records and business location details. These are the core resources that agents debate and act upon during their conversation.

Yes. The agent can call `create_contact` and validate the result immediately, ensuring the new record is properly established in the system before proceeding with other tasks.

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