How to Use the Bizzabo MCP in LlamaIndex

Index your Bizzabo event details into LlamaIndex for grounded, searchable knowledge.

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Connect Bizzabo MCP to LlamaIndex

Create your Vinkius account to connect Bizzabo 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 Bizzabo with LlamaIndex

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Search Bizzabo data with LlamaIndex

Call `list_speakers` and `list_sessions` to build a local vector index. Your agent then queries this knowledge base instead of guessing event times. It turns raw API output into a queryable format. You get answers based on your actual event data rather than model hallucinations.

Ground your agent in event facts

Use `get_event` to feed specific details into your RAG pipeline. The agent uses this as a source of truth for all user inquiries. This keeps your responses tied to current attendee lists. You avoid outdated information by pulling fresh data directly from the source.

Manage event knowledge in LlamaIndex

Filter tools to limit what the agent can access from Bizzabo. You decide which parts of the event metadata become searchable knowledge. This setup keeps your index clean and focused. It ensures the agent only retrieves relevant session or registration context when asked.

Setup guide

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

It uses the server to fetch data and index it into your vector store. Your agent then performs semantic searches across the event schedule.

You pull the registration list into the index and query it for specific attendee details. The agent synthesizes the data based on your prompt.

You trigger fresh pulls to update your index. This ensures the agent works with the latest session times and speaker rosters.

All traffic between the server and your index is encrypted. We handle the connection securely so your attendee records remain private.

Your registration records are processed in a transient memory sandbox. We never persist your attendee data, ensuring your private event lists remain under your control.

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