AudD Music Recognition MCP Server for LangChain 8 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect AudD Music Recognition through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"audd-music-recognition": {
"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 AudD Music Recognition, 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 AudD Music Recognition MCP Server
Equip your AI agent with the power of AudD, the leading music recognition and data platform. This integration allows your agent to identify songs from audio URLs, search for track information by title or artist, and retrieve full lyrics or snippets. Your agent can also find direct streaming links for identified tracks on platforms like Spotify and Apple Music. Whether you are identifying a background track from a video or searching for that one song with a specific lyric, your agent acts as a dedicated musicologist through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with AudD Music Recognition through native MCP adapters. Connect 8 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
- Music Recognition — Identify songs from publicly accessible audio URLs with high precision.
- Lyrics Search — Find full lyrics or search for songs using fragments of text.
- Metadata Retrieval — Fetch detailed track, artist, and album information including release dates and labels.
- Streaming Links — Get direct URLs to listen to identified tracks on major music platforms.
- Timecode Identification — Start recognition from a specific offset to identify songs in long audio files.
The AudD Music Recognition MCP Server exposes 8 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 AudD Music Recognition to LangChain via MCP
Follow these steps to integrate the AudD Music Recognition 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 8 tools from AudD Music Recognition via MCP
Why Use LangChain with the AudD Music Recognition MCP Server
LangChain provides unique advantages when paired with AudD Music Recognition through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine AudD Music Recognition 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 AudD Music Recognition queries for multi-turn workflows
AudD Music Recognition + LangChain Use Cases
Practical scenarios where LangChain combined with the AudD Music Recognition MCP Server delivers measurable value.
RAG with live data: combine AudD Music Recognition tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query AudD Music Recognition, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain AudD Music Recognition tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every AudD Music Recognition tool call, measure latency, and optimize your agent's performance
AudD Music Recognition MCP Tools for LangChain (8)
These 8 tools become available when you connect AudD Music Recognition to LangChain via MCP:
add_monitored_stream
Add an audio stream to monitor for music
get_lyrics
Get full lyrics for a specific track
list_monitored_streams
List all monitored audio streams
recognize_at_time
Useful for long files. Recognize music starting at a specific offset
recognize_music
Returns artist, title, album, and streaming links (Apple Music, Spotify, etc.). Recognize a song from an audio URL
search_lyrics
Returns matched lyrics and song metadata. Search for song lyrics by text fragment
search_music
Search for a song by text query
set_stream_callback_url
Set the webhook URL for stream monitoring results
Example Prompts for AudD Music Recognition in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with AudD Music Recognition immediately.
"Identify the song at this URL: https://example.com/audio.mp3"
"Search for lyrics containing 'never gonna give you up'."
"Find the artist and album for the song 'Stairway to Heaven'."
Troubleshooting AudD Music Recognition MCP Server with LangChain
Common issues when connecting AudD Music Recognition to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAudD Music Recognition + LangChain FAQ
Common questions about integrating AudD Music Recognition 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 AudD Music Recognition 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.
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
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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 AudD Music Recognition to LangChain
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.