How to Use the AppFollow MCP in AutoGen

Let your AutoGen agents debate and converge on decisions using live AppFollow store metrics.

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Connect AppFollow MCP to AutoGen

Create your Vinkius account to connect AppFollow 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 AppFollow with AutoGen

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Enable AutoGen agent debates with store data

Deploy a team of agents where one pulls `list_reviews` and another analyzes them. The agents challenge each other to reach a consensus on current user sentiment. This setup forces agents to justify their findings using the raw data provided. They negotiate until the team agrees on the final summary or trend analysis.

Automate AppFollow tool usage in AutoGen

The McpToolAdapter automatically maps server tools to your agent definitions. You pass the list to the AssistantAgent, and the system handles the communication automatically. Your agents invoke `get_rankings` or `get_app_info` as part of their conversation flow. They share the outputs, ensuring every agent has the same context for the discussion.

Use specialized agents for AppFollow tasks

Assign a security agent to flag risks in reviews and a performance agent to push for ranking improvements. They work together to address store issues. Because they debate, you get a balanced perspective. One agent might suggest acting on `get_reviews_ai_summary`, while another debates the urgency based on historical rating trends.

Setup guide

Set up AppFollow 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 AppFollow 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="AppFollow_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent AppFollow 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 AppFollow. 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 AppFollow MCP in AutoGen

Yes, once an agent calls a tool, the result becomes part of the shared conversation history. All agents in the group can then reference that data for their next move.

You provide the server URL to the adapter, which then converts the tools for your agents. The agents treat these tools as native functions within their conversation loop.

They do. If you have multiple agents, they will compare the data they pull and discuss the implications before presenting a final conclusion to you.

It supports both stdio and Streamable HTTP. Choose the one that fits your specific deployment architecture for your agent team.

Data is scoped strictly to the agents involved in your conversation. No review text or ranking data is shared outside your local system during the debate process.

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