How to Use the Deezer MCP in AutoGen

Q: How do AutoGen agents share Deezer data over MCP during a debate?

Agents pass the JSON outputs of tools like getartistradio to each other through the group chat history, allowing them to critique the recommendations.

Q: Can an AutoGen agent autonomously search for new music on Deezer?

Yes. You can register searchalbums as a tool, and the agent will call it whenever it needs to find new releases during a conversation.

Let your AutoGen agents debate and collaborate to build the ultimate curated playlists using live Deezer data.

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Create your Vinkius account to connect Deezer 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 Deezer with AutoGen

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Multi-agent Deezer playlist curation with AutoGen

Set up a group chat where one AutoGen agent acts as a music critic and another acts as a data gatherer. While the gatherer runs `search_tracks` to find Deezer options, the AutoGen critic analyzes the results to ensure they fit a specific vibe. These AutoGen agents collaborate to refine the selection, using `get_track` to check Deezer durations and preview links. Your final output is a highly curated Deezer playlist that has been critiqued and verified by autonomous AutoGen agents.

Resolve Deezer music debates using this MCP Server

When your AutoGen agents disagree on which Deezer artist is more popular, they can settle it using real numbers. One agent can call `get_artist` to pull fan counts, while another checks `get_artist_top_tracks` to compare recent performance. This consensus-driven AutoGen approach ensures your automated music reports are backed by live data. The agents negotiate the final list based on actual metrics from the Deezer MCP Server rather than guesswork.

Coordinate complex Deezer research with AutoGen

Divide and conquer your music research by assigning different AutoGen agents to specific Deezer tasks. One agent can focus on regional trends using `get_chart`, while another digs into genre history with `get_genre_playlists`. The AutoGen agents share their findings in a joint session, compiling a detailed report on current Deezer musical trends. It turns a complex Deezer research task into a structured conversation between specialized AutoGen agents.

Setup guide

Set up Deezer 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 Deezer 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="Deezer_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Agents pass the JSON outputs of tools like `get_artist_radio` to each other through the group chat history, allowing them to critique the recommendations.

Yes. You can register `search_albums` as a tool, and the agent will call it whenever it needs to find new releases during a conversation.

You set termination conditions or use a critic agent to stop the conversation once the required tracks from `search_playlists` are found.

Yes. You can connect to the server using the Streamable HTTP transport, letting your agents access all 14 music tools instantly.

Your artist searches, playlist details, and query histories are routed through an isolated V8 sandbox. This setup ensures that your raw music data is never exposed to external actors or stored on disk.

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