How to Use the Castmagic MCP in LlamaIndex

Index your transcripts into LlamaIndex using the Castmagic MCP Server.

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Connect Castmagic MCP to LlamaIndex

Create your Vinkius account to connect Castmagic 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.

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Setup Castmagic with LlamaIndex

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Ingest media data into LlamaIndex

Use `get_transcript_details` to pull raw text into your vector store. LlamaIndex then indexes this content for semantic retrieval across your entire knowledge base. This turns your audio library into a queryable asset. You stop hunting for files and start asking questions about what was actually said.

Refine LlamaIndex knowledge with speaker data

Call `list_transcript_speakers` to map metadata to your indexed chunks. It adds a layer of context that makes your RAG queries far more precise. Your index now understands who said what. You can filter retrieval results by specific participants to ground your agent's answers.

Query Castmagic records in LlamaIndex

Keep your index fresh by running `list_transcripts` to discover new uploads. It ensures your RAG pipeline always reflects the latest available audio data. Automate the update process by scheduling these calls. Your agent stays current without you lifting a finger.

Setup guide

Set up Castmagic MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
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 provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to 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 Castmagic MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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 Castmagic tools.",
)
response = await agent.run("List recent Castmagic data")

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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 Castmagic. 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 Castmagic MCP in LlamaIndex

You fetch the transcript text using the tool and pass it to your LlamaIndex node parser. This allows the framework to embed the content into your vector store.

Once indexed, you can run natural language queries against your transcripts. LlamaIndex uses the text retrieved from the server to provide accurate, grounded answers.

Your audio and transcript files remain strictly private to your account. Only your LlamaIndex instance can retrieve the data, and it is never shared with other users.

You can re-run the tool call to pull the latest version and update your index. LlamaIndex handles the document replacement to keep your knowledge base clean.

Yes, you can pull transcripts individually or in batches. This keeps your memory usage predictable while building large-scale knowledge bases.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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