How to Use the join.me MCP in LlamaIndex

Q: Can LlamaIndex query specific join.me meeting details?

Yes. The agent fires getmeeting to pull the exact parameters of a single session. It then embeds that JSON response into your vector store.

Q: Does the join.me integration support ad-hoc rooms in LlamaIndex?

It does. You trigger startadhocmeeting to generate an instant browser link. The generated URL becomes an immediate fact in your RAG index.

Index your join.me meeting history into searchable vector stores with LlamaIndex.

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Connect join.me MCP to LlamaIndex

Create your Vinkius account to connect join.me 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 join.me with LlamaIndex

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Semantic Search for Meetings

The `list_meetings` tool pulls your entire session history directly into your LlamaIndex knowledge base. Your RAG application ingests times, titles, and participant metrics as queryable document nodes. Users ask questions about past syncs and get answers grounded in actual API data. The system reads the exact output of `get_meeting` instead of hallucinating details about who attended what.

LlamaIndex MCP Server Context

You execute `get_user_info` to append account profile data to your current index context. This allows your agent to cross-reference the host's details against their scheduled sessions. The framework stores these profile metrics alongside active session data. When a user asks about their upcoming schedule, the RAG pipeline retrieves the exact records instantly.

Live Session Grounding

Running `start_scheduled_meeting` initiates a planned room while logging the activation event to your RAG store. The agent tracks which sessions actually started versus those that were just planned. You also index your event architecture by calling `list_webhooks`. This creates a semantic map of your notification triggers, letting developers query their own infrastructure setup.

Setup guide

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

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Common questions about join.me MCP in LlamaIndex

Run pip install llama-index-tools-mcp first. Initialize BasicMCPClient, wrap it in McpToolSpec, and pass the resulting tool list to your FunctionAgent.

Yes. The agent fires get_meeting to pull the exact parameters of a single session. It then embeds that JSON response into your vector store.

It does. You trigger start_adhoc_meeting to generate an instant browser link. The generated URL becomes an immediate fact in your RAG index.

Your agent retrieves the target ID from the vector database and executes delete_meeting. The index updates automatically to reflect the canceled status.

The integration touches user profile metadata and meeting schedules. All traffic routes through a zero-trust gateway that requires explicit endpoint tokens for every request.

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