Deezer MCP Server for LangChain 14 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Deezer through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"deezer": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Deezer, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Deezer MCP Server
Connect Deezer music catalog to any AI agent and search millions of tracks, discover artists, explore albums and playlists, and check global charts through natural language.
LangChain's ecosystem of 500+ components combines seamlessly with Deezer through native MCP adapters. Connect 14 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Track Search — Search millions of tracks by title, lyrics, or keywords with preview links
- Artist Discovery — Find artists, view fan counts, and get their top tracks and radio stations
- Album Browsing — Look up albums by title or artist with release dates and track listings
- Playlist Exploration — Search public playlists by mood, genre, or curator
- Charts — Check top tracks, albums, artists, and playlists globally or by country
- Genre Navigation — Browse music genres and find curated playlists per genre
The Deezer MCP Server exposes 14 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Deezer to LangChain via MCP
Follow these steps to integrate the Deezer MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 14 tools from Deezer via MCP
Why Use LangChain with the Deezer MCP Server
LangChain provides unique advantages when paired with Deezer through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Deezer MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Deezer queries for multi-turn workflows
Deezer + LangChain Use Cases
Practical scenarios where LangChain combined with the Deezer MCP Server delivers measurable value.
RAG with live data: combine Deezer tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Deezer, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Deezer tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Deezer tool call, measure latency, and optimize your agent's performance
Deezer MCP Tools for LangChain (14)
These 14 tools become available when you connect Deezer to LangChain via MCP:
get_album
Get detailed album information
get_album_tracks
Get tracks from an album
get_artist
Get detailed artist information
get_artist_radio
Get artist radio tracks
get_artist_top_tracks
Get top tracks for an artist
get_chart
Optionally filter by country using ISO 3166-1 country code. Get Deezer charts
get_genre
Get genre information
get_genre_playlists
Get playlists for a genre
get_playlist
Get detailed playlist information
get_track
Get detailed track information
search_albums
Returns albums with release date, track count, and cover art info. Search for albums on Deezer
search_artists
Returns artist info including fan count, album count, and profile links. Search for artists on Deezer
search_playlists
Returns playlist info including creator, track count, and fan count. Search for playlists on Deezer
search_tracks
Returns tracks with title, artist, album, duration, and preview link. Supports pagination with limit and offset index. Search for tracks on Deezer
Example Prompts for Deezer in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Deezer immediately.
"Search for songs by Daft Punk."
"What's trending in Brazil right now?"
"Find me chill playlists for studying."
Troubleshooting Deezer MCP Server with LangChain
Common issues when connecting Deezer to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersDeezer + LangChain FAQ
Common questions about integrating Deezer MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Deezer with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Deezer to LangChain
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.