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How to Use the Accelevents MCP in LlamaIndex

Turn your Accelevents event history into a searchable knowledge base with LlamaIndex.

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LlamaIndex

Connect Accelevents MCP to LlamaIndex

Create your Vinkius account to connect Accelevents 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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Index Your Event Data

Stop hitting the API for every single question. With LlamaIndex, you can use the Accelevents tools to build a persistent, queryable index of your event data. Run a simple script to periodically call `list_events`, `list_sessions`, and `list_exhibitors`. LlamaIndex takes that output and feeds it into a vector store you control. Now you have a knowledge base. Your agent can query that index for information instead of making live API calls every time someone asks a question.

Get Answers Grounded in Fact

This is how you build a RAG pipeline that doesn't hallucinate. When you ask your agent, "Which speakers discussed data engineering at last year's summit?", it's not guessing. It's performing a semantic search against the real session data it indexed from `list_sessions`. The agent can retrieve the exact session details and cite its sources. It's answering questions based on a snapshot of your actual Accelevents history, which makes the answers trustworthy. This MCP server provides the raw data to make it happen.

Query Your MCP Server with Natural Language

The tools in this MCP server become functions your LlamaIndex agent can call directly. You don't need to write specific code to handle each endpoint. Just ask a question. If the answer isn't in the index, the agent is smart enough to call the live API. For example, asking for the latest attendee count will trigger a fresh call to `list_attendees` to get you the most current information.

Setup guide

Set up Accelevents MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 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. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all Accelevents MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 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 Accelevents tools.",
)
response = await agent.run("List recent Accelevents data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Accelevents. 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 Accelevents MCP in LlamaIndex

You can use LlamaIndex to index all your past event data from Accelevents via this MCP server. Then, you can ask natural language questions like "what were our most popular sessions in 2023?" or "list all exhibitors from the New York event."
LlamaIndex itself doesn't store data. It creates an index from the data you fetch and stores it in a vector database that you control, like ChromaDB or Pinecone.
Querying the index is faster and cheaper for historical data. Calling the API via the Accelevents tools gets you real-time data, like the current number of attendees for an active event. LlamaIndex agents can decide which to use.
Yes. The LlamaIndex MCP adapter lets you provide an `allowed_tools` list. You can restrict an agent to only use `list_sessions`, for example, if you don't want it accessing attendee information.
Your agent will handle data about your events, sessions, exhibitors, and attendees fetched from the Accelevents API. The connection is secured by Vinkius, and the data is only passed to the LlamaIndex components and vector store you configure.

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