3Scribe MCP Server for LlamaIndex 4 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add 3Scribe as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to 3Scribe. "
"You have 4 tools available."
),
)
response = await agent.run(
"What tools are available in 3Scribe?"
)
print(response)
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 3Scribe MCP Server
Unlock the power of spoken word with 3Scribe, your automated partner for high-precision audio and video transcription. By connecting 3Scribe to your AI agent, you eliminate the friction of manual data entry from media files. Your agent can now orchestrate the entire transcription lifecycle—from submitting public URLs to auditing job statuses and retrieving final text—all through simple natural language commands. Whether it’s meeting minutes or video captions, your agent acts as a direct bridge to 3Scribe's powerful recognition engine.
LlamaIndex agents combine 3Scribe tool responses with indexed documents for comprehensive, grounded answers. Connect 4 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Automated Transcription — Create new transcription jobs by providing a public URL to your audio or video files
- Job Monitoring — Track the status of your transcriptions in real-time (Requested, Processing, Completed, Error)
- Text Retrieval — Access raw text transcripts or detailed word-level data with timestamps and speaker IDs
- Project Management — List all transcription jobs, filter by status, and delete old or unnecessary projects
- Language Detection — Specify transcription languages or let the AI auto-detect the spoken language
The 3Scribe MCP Server exposes 4 tools through the Vinkius. Connect it to LlamaIndex 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 3Scribe to LlamaIndex via MCP
Follow these steps to integrate the 3Scribe MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 4 tools from 3Scribe
Why Use LlamaIndex with the 3Scribe MCP Server
LlamaIndex provides unique advantages when paired with 3Scribe through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine 3Scribe tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain 3Scribe tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query 3Scribe, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what 3Scribe tools were called, what data was returned, and how it influenced the final answer
3Scribe + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the 3Scribe MCP Server delivers measurable value.
Hybrid search: combine 3Scribe real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query 3Scribe to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying 3Scribe for fresh data
Analytical workflows: chain 3Scribe queries with LlamaIndex's data connectors to build multi-source analytical reports
3Scribe MCP Tools for LlamaIndex (4)
These 4 tools become available when you connect 3Scribe to LlamaIndex via MCP:
create_job
You must provide a valid public URL. Returns a Job ID useful for tracking progress. Initiate a new audio or video transcription job in 3Scribe via a public media URL
delete_job
This is an irreversible destructive action. Requires the Job ID. Permanently delete a transcription task and its associated data from the 3Scribe account
get_job
You must provide the Job ID. Check the status and retrieve the generated text of a specific 3Scribe transcription job
list_jobs
Retrieve a paginated list of all transcription tasks from the 3Scribe account
Example Prompts for 3Scribe in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with 3Scribe immediately.
"Transcribe the audio from this URL: https://example.com/podcast.mp3"
"What is the status of my transcription job 54321?"
"Delete my old transcription job with ID 99999."
Troubleshooting 3Scribe MCP Server with LlamaIndex
Common issues when connecting 3Scribe to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcp3Scribe + LlamaIndex FAQ
Common questions about integrating 3Scribe MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect 3Scribe 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 3Scribe to LlamaIndex
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.