How to Use the 7digital MCP in LlamaIndex
Index your entire 7digital music library into LlamaIndex for semantic search and grounded responses.
Works with every AI agent you already use
…and any MCP-compatible client
Connect 7digital MCP to LlamaIndex
Create your Vinkius account to connect 7digital to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Index 7digital data for LlamaIndex
Feed the output of `get_artist_releases` and `get_release_tracks` directly into your vector store. LlamaIndex turns these API responses into a searchable knowledge base. You stop relying on generic agent memory. Instead, you query your indexed 7digital catalog to get precise answers about discographies and track details grounded in actual API results.
Automate discovery with LlamaIndex
Use `search_artist` to gather context that LlamaIndex then indexes. When you ask about an artist, the agent searches your local vector store first, then hits the live API if needed. This approach reduces hallucination significantly. You get accurate track lists and metadata because the agent compares its internal index against the live server data.
Build RAG apps with 7digital and LlamaIndex
Combine your local documents with live 7digital catalog data. The `get_release_details` tool provides the fresh metadata your RAG pipeline requires to stay current. Your application indexes the latest release information as it arrives. You define which tools are allowed, keeping the agent focused on specific catalog segments.
Set up 7digital MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports. - 3
Convert to LlamaIndex tools
Call
mcp_tool_spec.to_tool_list_async()to convert all 7digital MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
# Connect to the MCP
mcp_client = BasicMCPClient(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()
# Create and run the agent
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt="You have access to 7digital tools.",
)
response = await agent.run("List recent 7digital data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by 7digital. 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.
Why Choose Vinkius
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Common questions about 7digital MCP in LlamaIndex
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