How do I find my Airmeet Access and Secret Keys?

Log in to your Airmeet Dashboard, navigate to **Integrations** > **API Access Key**, and click on 'Generate Key'. You will receive both the Access Key and Secret Key there.

Can I retrieve magic links for attendees?

Yes! When you use the `add_attendee` tool, Airmeet generates a unique entry link. You can also use the `list_participants` tool to retrieve existing magic links for registered users.

How long are recording links valid?

Recording download links retrieved via the `get_session_recordings` tool are temporary and typically remain valid for 6 hours. We recommend downloading the media immediately.

Airmeet MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Airmeet
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Airmeet as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Airmeet. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Airmeet?"
    )
    print(response)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Airmeet MCP Server

Connect your Airmeet community to your AI agent to unlock professional event orchestration and attendee management. From creating new virtual events and sessions to auditing attendee lists and retrieving session recordings, your agent handles your event lifecycle through natural conversation.

LlamaIndex agents combine Airmeet tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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

Event Orchestration — Create and configure Airmeet events, manage sessions, and update event statuses (start, pause, end)
Attendee Management — Add authorized attendees, retrieve magic links, and audit participant lists for any event
Speaker Coordination — Add and manage speakers for your event sessions seamlessly
Engagement Auditing — Retrieve analytics for event attendance, poll responses, and questions asked by participants
Media Access — Retrieve download links for session recordings to support your post-event content strategy

The Airmeet MCP Server exposes 10 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 Airmeet to LlamaIndex via MCP

Follow these steps to integrate the Airmeet 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 10 tools from Airmeet

Why Use LlamaIndex with the Airmeet MCP Server

LlamaIndex provides unique advantages when paired with Airmeet through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Airmeet tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Airmeet tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Airmeet, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Airmeet tools were called, what data was returned, and how it influenced the final answer

Airmeet + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Airmeet MCP Server delivers measurable value.

Hybrid search: combine Airmeet real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Airmeet 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 Airmeet for fresh data

Analytical workflows: chain Airmeet queries with LlamaIndex's data connectors to build multi-source analytical reports

Airmeet MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Airmeet to LlamaIndex via MCP:

add_attendee

create_event

Create a new Airmeet

create_session

Add a session to event

get_event_attendance

Get attendance analytics

get_session_recordings

Get recording download links

list_events

List virtual events

list_participants

List event participants

list_poll_responses

List event polls

list_questions

List participant questions

update_event_status

Change event status

Example Prompts for Airmeet in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Airmeet immediately.

"List all Airmeet events scheduled for next month."

"Add 'John Doe' (john@example.com) as an attendee to event ID 12345."

"Retrieve the recordings for session ID 98765."

Troubleshooting Airmeet MCP Server with LlamaIndex

Common issues when connecting Airmeet to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Airmeet + LlamaIndex FAQ

Common questions about integrating Airmeet MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Airmeet tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.