AssemblyAI MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add AssemblyAI as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 AssemblyAI. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in AssemblyAI?"
)
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 AssemblyAI MCP Server
Empower your AI agent to orchestrate your entire audio intelligence and transcription workflow with AssemblyAI, the leading platform for speech-to-text. By connecting AssemblyAI to your agent, you transform complex audio processing into a natural conversation. Your agent can instantly start transcription jobs from any URL, audit transcript results with high confidence, and manage job history without you ever touching a technical console. Whether you are analyzing podcast content or transcribing meetings, your agent acts as a real-time linguistic assistant, ensuring your audio data is always accessible and searchable.
LlamaIndex agents combine AssemblyAI tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Transcription Auditing — Start transcription jobs for any audio or video URL and retrieve cleaned text with speaker labels.
- Linguistic Oversight — Retrieve transcripts broken down by sentences or paragraphs to maintain a structured view of spoken content.
- Status Intelligence — Monitor the progress of long-running transcription jobs to ensure timely data delivery.
- Execution Management — List all past and active transcripts to maintain strict organizational control over your audio assets.
- Confidence Intelligence — Retrieve confidence scores for each transcription to verify the accuracy of your linguistic data.
The AssemblyAI MCP Server exposes 6 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 AssemblyAI to LlamaIndex via MCP
Follow these steps to integrate the AssemblyAI 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 6 tools from AssemblyAI
Why Use LlamaIndex with the AssemblyAI MCP Server
LlamaIndex provides unique advantages when paired with AssemblyAI through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine AssemblyAI tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain AssemblyAI tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query AssemblyAI, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what AssemblyAI tools were called, what data was returned, and how it influenced the final answer
AssemblyAI + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the AssemblyAI MCP Server delivers measurable value.
Hybrid search: combine AssemblyAI real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query AssemblyAI 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 AssemblyAI for fresh data
Analytical workflows: chain AssemblyAI queries with LlamaIndex's data connectors to build multi-source analytical reports
AssemblyAI MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect AssemblyAI to LlamaIndex via MCP:
delete_transcript
Delete a transcription record
get_transcript
Get the result of a transcription job
get_transcript_paragraphs
Get the transcript broken down by paragraphs
get_transcript_sentences
Get the transcript broken down by sentences
list_transcripts
List all transcription jobs
transcribe_audio
Start a transcription job for an audio/video URL
Example Prompts for AssemblyAI in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with AssemblyAI immediately.
"Transcribe the audio file at https://example.com/podcast.mp3 using AssemblyAI."
"Show me the result for transcript ID xxxx."
"List all my past AssemblyAI transcripts."
Troubleshooting AssemblyAI MCP Server with LlamaIndex
Common issues when connecting AssemblyAI to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAssemblyAI + LlamaIndex FAQ
Common questions about integrating AssemblyAI 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 AssemblyAI 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 AssemblyAI to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.