How do I find my MeetingPulse API Key?

Log in to MeetingPulse, go to your Profile or Integration Settings, and generate or copy your API Key from the API section.

Can I retrieve poll results in real-time?

Yes! Use the `get_poll_details` tool with the meeting and poll IDs to see the current voting results.

Is my meeting data secure?

Absolutely. Your credentials are encrypted at rest and injected securely at runtime.

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

Name: MeetingPulse
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 MeetingPulse 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 MeetingPulse. "
            "You have 10 tools available."
        ),
    )

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

asyncio.run(main())

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About MeetingPulse MCP Server

Connect your MeetingPulse account to any AI agent and take full control of your audience engagement and meeting data through natural conversation.

LlamaIndex agents combine MeetingPulse 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

Meeting Oversight — List all active and past meetings and fetch detailed configuration and status
Poll Monitoring — Retrieve poll results, individual questions, and survey summaries in real-time
Engagement Analytics — Access meeting engagement metrics and participant analytics instantly
Interaction Tracking — Monitor Q&A sessions and list attendees for specific meetings
Resource Management — List files and materials shared during your interactive sessions

The MeetingPulse 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 MeetingPulse to LlamaIndex via MCP

Follow these steps to integrate the MeetingPulse 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 MeetingPulse

Why Use LlamaIndex with the MeetingPulse MCP Server

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

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

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

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

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

MeetingPulse + LlamaIndex Use Cases

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

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

Data enrichment: query MeetingPulse 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 MeetingPulse for fresh data

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

MeetingPulse MCP Tools for LlamaIndex (10)

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

get_account_info

Get account information

get_meeting

Get details for a specific meeting

get_meeting_analytics

Get meeting analytics

get_poll_details

Get details for a specific poll

list_attendees

List meeting attendees

list_meeting_files

List files shared in a meeting

list_meetings

List all meetings

list_polls

List polls for a meeting

list_qa_sessions

List Q&A sessions

search_meetings

Search meetings by term

Example Prompts for MeetingPulse in LlamaIndex

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

"List all active meetings in MeetingPulse."

"Show results for the poll 'Favorite Feature' in meeting ID 123."

"Get engagement analytics for meeting ID 123."

Troubleshooting MeetingPulse MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

MeetingPulse + LlamaIndex FAQ

Common questions about integrating MeetingPulse 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 MeetingPulse tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.