How to Use the Adobe Analytics MCP in AutoGen

Debate your data using AutoGen agents and the Adobe Analytics MCP Server.

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Connect Adobe Analytics MCP to AutoGen

Create your Vinkius account to connect Adobe Analytics 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 Adobe Analytics with AutoGen

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Perplexity

AutoGen agents debating Adobe Analytics data

Assign one agent to fetch `get_report` data and another to critique the findings. They negotiate the interpretation of your metrics until they reach a consensus. This prevents single-point-of-failure logic. You get a more thorough analysis because the agents challenge each other's assumptions based on the raw API output.

Negotiated report suite analysis

Use `list_report_suites` to feed the team of agents the available options. One agent proposes a suite, while the security agent verifies if it's the right one for the task. This creates a system where decisions are backed by deliberation. You aren't just getting a raw JSON dump; you're getting a vetted conclusion from your agent team.

Multi-agent tool execution

The AutoGen framework automatically maps these tools to your assistant agents. They decide when to pull `get_dimensions` to clarify a report. Your agents handle the schema conversion internally. You just define the team and let them call the server as needed to finish the job.

Setup guide

Set up Adobe Analytics 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 Adobe Analytics 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="Adobe Analytics_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You pass the tool list to your AssistantAgent constructor. The framework handles the communication so that any agent in your team can invoke the server tools.

Yes, you set up a group chat where one agent retrieves the metrics and another analyzes them. They can debate the results until they agree on the final summary.

All five tools, including report retrieval and segment listing, are available. Your agents can call these in any sequence required by your conversation flow.

It supports both stdio and HTTP transports through the extension package. You configure the server parameters once, and the agents handle the connections automatically.

The server acts as a secure intermediary for your agent team. Your API token stays on the Vinkius-managed host, and only the requested report data is exposed to your agents.

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