How to Use the 3Scribe MCP in LlamaIndex

Q: Does 3Scribe support LlamaIndex filtering?

You can use the allowedtools filter to restrict which operations your agent performs. It keeps your index build process predictable.

Q: How do I check 3Scribe status in LlamaIndex?

Use the getjob tool to poll the status of your task. Your agent will know exactly when the text is ready for ingestion.

Index your transcripts into LlamaIndex for grounded, searchable knowledge.

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Connect 3Scribe MCP to LlamaIndex

Create your Vinkius account to connect 3Scribe 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 3Scribe with LlamaIndex

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Automate indexing with LlamaIndex

Trigger `create_job` to get your audio content ready for the engine. The server handles the heavy lifting of transcription behind the scenes. Once finished, you pull the text and pass it to your index. This connects raw media to your searchable knowledge base.

Fetch transcripts for your LlamaIndex RAG

Your agent uses `get_job` to retrieve the text output. It then updates your vector store with fresh, accurate data. This removes the need for manual copy-pasting. You build a system that learns from every audio file you process.

Manage your LlamaIndex data source

Call `list_jobs` to verify which files are indexed in your account. It keeps your knowledge base synced with your actual 3Scribe history. Use `delete_job` to prune old entries. You ensure your RAG application only references the data you currently need.

Setup guide

Set up 3Scribe 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 3Scribe 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 3Scribe tools.",
)
response = await agent.run("List recent 3Scribe 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 3Scribe. 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 3Scribe MCP in LlamaIndex

You use the standard tool spec to wrap the server functions. Once connected, your agent treats 3Scribe operations like native LlamaIndex functions.

Yes, you can chain the retrieval tool with your indexing logic. The agent pulls the text and commits it to your store in one flow.

You can use the allowed_tools filter to restrict which operations your agent performs. It keeps your index build process predictable.

Use the `get_job` tool to poll the status of your task. Your agent will know exactly when the text is ready for ingestion.

We process your media files in a sandboxed environment dedicated to your account. Your transcription results are kept behind your unique endpoint token.

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