How to Use the Adobe Customer Journey Analytics (CJA) MCP in AutoGen

Enable multi-agent debates over Adobe Customer Journey Analytics (CJA) reports inside AutoGen.

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Connect Adobe Customer Journey Analytics (CJA) MCP to AutoGen

Create your Vinkius account to connect Adobe Customer Journey Analytics (CJA) 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 Customer Journey Analytics (CJA) with AutoGen

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Debate omnichannel performance using AutoGen agents

Your AutoGen agents invoke `get_report` to analyze customer touchpoints across multiple channels. A data agent pulls the report, while an optimization agent critiques the results to find friction points. This collaborative process ensures your analytics aren't just read, but actively debated. You get automated insights that have been pressure-tested by competing LLM personas.

Resolve schema conflicts with this MCP Server

This MCP Server uses `list_data_views` to let your AutoGen agents check active configurations. When agents disagree on which data view to query, they inspect the live list to reach a consensus. The debate is resolved programmatically without human intervention. Your agents dynamically select the correct data view based on the specific metrics required for their task.

Validate journey filters through agent consensus

The `list_filters` tool allows your agents to review existing segments before running reports. An analyst agent checks the filters to ensure the target audience matches the campaign goals. If the performance agent flags an issue, they run `get_data_view_dimensions` to suggest filter adjustments. The entire negotiation happens in the background, outputting a refined strategy.

Setup guide

Set up Adobe Customer Journey Analytics (CJA) 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 Customer Journey Analytics (CJA) 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 Customer Journey Analytics (CJA)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Adobe Customer Journey Analytics (CJA) 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 CJA. 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 Customer Journey Analytics (CJA) MCP in AutoGen

You register the MCP Server tools using the AutoGen MCP adapter and pass them to your AssistantAgent. This makes tools like `get_report` available during agent conversations.

Yes, the Streamable HTTP transport handles concurrent requests. Multiple agents can query different data views or metrics simultaneously during their debate.

You can configure a supervisor agent to approve tool calls before they execute. This ensures `get_report` is only called when the agents have agreed on the exact parameters.

Yes, the AutoGen MCP adapter automatically translates the server's JSON schemas into the format AutoGen expects. You do not need to write any manual schema conversion code.

Vinkius manages your API credentials securely, exposing only a single endpoint token to your AutoGen environment. Your actual Adobe keys, data views, and reports never enter the agent conversation or logs.

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