How to Use the Jamendo MCP in OpenAI Agents SDK

Q: How do I initialize the Jamendo MCP Server in my OpenAI Agents SDK project?

Install the package first. Use MCPServerStreamableHttp with your Vinkius connection URL and register it inside your Python agent's mcpservers list.

Q: Does the Jamendo integration support autocomplete search?

It does. Your agent can call autocompletesearch to get instant prefix-based matches for artists or tags, making search queries faster and more accurate.

Give your OpenAI Agents SDK production deployment direct programmatic access to Jamendo's music catalog.

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Connect Jamendo MCP to OpenAI Agents SDK

Create your Vinkius account to connect Jamendo to OpenAI Agents SDK 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 Jamendo with OpenAI Agents SDK

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Smart Track Discovery with OpenAI Agents SDK

This Jamendo MCP Server exposes the `search_tracks` and `search_artists` tools directly to your agent constructors. Your deployed OpenAI Python agents can search the Jamendo catalog, find specific tracks, and map out artist catalogs on the fly. To keep your OpenAI Agents SDK performance tight, you can cache these Jamendo tools. Your OpenAI agent uses `get_artist_albums` to find a Jamendo artist's discography and then pulls individual tracks with `get_album_tracks` without manual routing.

Build Playlists with Guardrails

You can manage Jamendo user libraries using `set_user_favorite` and `set_user_playlist` while keeping your OpenAI execution safe. The OpenAI platform lets you set strict verification guardrails before your agent modifies a user's actual Jamendo account. Your OpenAI agents can read current user preferences through `get_user_tracks` and `get_user_albums`. If a track doesn't fit the vibe, the agent calls `set_user_dislike` to train the recommendation loop, all tracked in your OpenAI dashboard.

Real-Time Radio Feeds

This MCP integration lets your OpenAI Agents SDK pull live audio streams using `get_radio_stream` and `list_radios`. Your specialized OpenAI agents can hand off tasks to each other, passing radio metadata to build continuous background music features. The OpenAI agent checks what's currently playing on Jamendo and pulls similar music using `get_similar_tracks`. If users want to go deeper, the agent queries `get_track_reviews` to summarize community feedback before updating the queue.

Setup guide

Set up Jamendo MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Jamendo tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Jamendo tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Jamendo tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Jamendo Agent",
            instructions="You have access to Jamendo tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 Jamendo. 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 Jamendo MCP in OpenAI Agents SDK

Install the package first. Use `MCPServerStreamableHttp` with your Vinkius connection URL and register it inside your Python agent's `mcp_servers` list.

Yes, you can control tool exposure at the agent constructor level. If you only want your OpenAI agent to read data, expose `search_tracks` and `get_track_reviews` while omitting the write tools.

The server handles OAuth2 tokens securely. When your agent calls `set_user_like` or `set_user_favorite`, Vinkius routes the authenticated request to Jamendo's API.

It does. Your agent can call `autocomplete_search` to get instant prefix-based matches for artists or tags, making search queries faster and more accurate.

Your authentication tokens and user favorite selections are never stored in plain text. Vinkius runs this server inside an isolated sandboxed environment, meaning your credentials never leak to the LLM or external logs.

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