How to Use the Appfigures MCP in AutoGen

Debate your Appfigures metrics using AutoGen agents for smarter business decisions.

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Connect Appfigures MCP to AutoGen

Create your Vinkius account to connect Appfigures 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 Appfigures with AutoGen

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Debate Appfigures data with AutoGen

Set up a performance agent and a finance agent to discuss `get_revenue_report` results. They compare current sales against historical trends to find anomalies. This setup allows agents to challenge each other's interpretation of your downloads and returns. You get a consensus view instead of just a raw data dump.

Cross-reference Appfigures with AutoGen

Instruct your agents to use `get_ranks` alongside `list_reviews` to see if ranking drops correlate with negative user feedback. The agents negotiate to determine the most likely cause. This multi-agent process helps clarify complex problems. You don't have to manually correlate store data when your agents do the heavy lifting.

Manage Appfigures connections in AutoGen

Use `get_external_accounts` to identify all linked stores. Your agents then coordinate to pull data from every source in a single conversation. This MCP server handles the heavy lifting of API communication. AutoGen simply manages the dialogue between your team of agents.

Setup guide

Set up Appfigures 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 Appfigures 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="Appfigures_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

They use the MCP adapter to translate your requests into tool calls. Each agent can then propose, execute, and verify the data retrieved from the server.

That is the point. You can assign different roles, like a skeptic and an analyst, to ensure the data is thoroughly reviewed before you see the final conclusion.

It is fully supported via the mcp-ext package. The adapter maps the 11 available tools directly into the agent's capability list.

If a tool call fails, the agents discuss the error. They can retry, check account status with `get_account_check`, or alert you to the problem.

The server acts as a gatekeeper. Your credentials and store tokens remain protected, with the agents only seeing the specific data returned by the tool calls.

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