How to Use the Eventtia MCP in LlamaIndex

Q: How can I use Eventtia and LlamaIndex to find past event details?

Ingest the output of listallevents and geteventdetaileddata into a LlamaIndex vector index. Once indexed, you can ask your agent questions like "what was the setup for the 'Q3 Summit'?" and get answers based on the actual configuration data pulled through the MCP server.

Q: Can I query B2B meeting data from Eventtia with LlamaIndex?

Absolutely. Point the McpToolSpec at this server. Your agent can then call listeventbusinessmeetings and index the results, letting you search for specific meetings or analyze networking patterns across events.

Q: How do I check my Eventtia account status with a LlamaIndex agent?

The agent can call the geteventtiaaccountmetadata tool directly. This gives it immediate access to your account limits and status, which you can use to build alerts or checks into your RAG application.

Ground your LlamaIndex RAG apps in real-time event data from Eventtia. Query your events, don't just call APIs.

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Connect Eventtia MCP to LlamaIndex

Create your Vinkius account to connect Eventtia 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 Eventtia with LlamaIndex

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Index Your Entire Event History

Use the `McpToolSpec` to turn all ten Eventtia tools into a queryable source. Run a script to fetch data from `list_all_events`, `list_event_sessions`, and `list_event_attendees` across your account. LlamaIndex will ingest and index this data automatically. Now you can ask natural language questions like, "who were our most frequent speakers last quarter?" Your agent finds the answer by searching the indexed data from `list_event_speakers`, not by guessing.

Query Live Events with LlamaIndex

Your agent can use `list_currently_live_events` to find what's happening right now. It then uses tools like `list_event_attendees` and `list_event_sessions` to fetch the latest data and update its knowledge index on the fly. This gives you a RAG system that's always current. Ask "who is speaking in the main hall?" and your LlamaIndex agent checks its index—just updated with live data—to give you a grounded answer. It's a direct link between your questions and the state of your event.

Turn Engagement Metrics into Knowledge with this MCP Server

Connect LlamaIndex to the `quick_event_engagement_audit` and `get_event_performance_stats` tools. You can build a system that periodically fetches these metrics, indexes them, and lets you track performance trends over time. Instead of just seeing a number, you can ask your agent "show me the engagement audit for our top 5 events this year." It will query the indexed history of your Eventtia data to provide a concrete, data-backed report. This turns raw API output into an actual knowledge base.

Setup guide

Set up Eventtia 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 Eventtia 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 Eventtia tools.",
)
response = await agent.run("List recent Eventtia data")

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Common questions about Eventtia MCP in LlamaIndex

Ingest the output of `list_all_events` and `get_event_detailed_data` into a LlamaIndex vector index. Once indexed, you can ask your agent questions like "what was the setup for the 'Q3 Summit'?" and get answers based on the actual configuration data pulled through the MCP server.

Absolutely. Point the `McpToolSpec` at this server. Your agent can then call `list_event_business_meetings` and index the results, letting you search for specific meetings or analyze networking patterns across events.

LlamaIndex turns the raw data from the MCP Server into a queryable knowledge base. You're not just getting a JSON response; you're building a system that can reason about your event history and provide contextually relevant answers.

The agent can call the `get_eventtia_account_metadata` tool directly. This gives it immediate access to your account limits and status, which you can use to build alerts or checks into your RAG application.

Your LlamaIndex application will access your Eventtia event data, including attendee lists, meeting schedules, and speaker information. It's up to you where you store the resulting index, but the MCP server itself is stateless and processes data in a secure sandbox per request.

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