Can I see the list of attendees for a specific event?

Yes! Use the `list_event_attendees` tool with the Event ID. Your agent will fetch the full list of community members registered for that event.

How do I find community chapters in a specific region?

Simply ask the agent to `search_chapters` with the region name as a query. It will retrieve all matching community groups located in that area.

Does the integration allow me to update event details?

Currently, the toolset focuses on querying and monitoring (Read-Only). You can list and inspect events, attendees, and chapters, but creation or modification must be done through the Bevy HQ dashboard for security.

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

Name: Bevy Community
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 Bevy Community 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 Bevy Community. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Bevy Community?"
    )
    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 Bevy Community MCP Server

Connect your Bevy Community account to any AI agent and orchestrate your virtual and in-person event workflows through natural conversation.

LlamaIndex agents combine Bevy Community 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 Oversight — List and inspect all community events, including dates, locations, and descriptions.
Chapter Management — Access and manage community chapters (groups) and their regional distribution.
Attendee Analysis — Retrieve lists of attendees for specific events to monitor community growth.
Event Discovery — Search for events and chapters using keywords to find relevant community activities.
Metric Tracking — Get real-time counts of events by status (upcoming, completed, etc.) for reporting.
User Insights — List which chapters a specific user belongs to for better community mapping.

The Bevy Community 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 Bevy Community to LlamaIndex via MCP

Follow these steps to integrate the Bevy Community 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 Bevy Community

Why Use LlamaIndex with the Bevy Community MCP Server

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

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

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

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

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

Bevy Community + LlamaIndex Use Cases

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

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

Data enrichment: query Bevy Community 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 Bevy Community for fresh data

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

Bevy Community MCP Tools for LlamaIndex (10)

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

get_chapter

Get specific chapter details

get_event

Get specific event details

get_event_counts

Retrieve counts of events by status

list_chapters

List all community chapters

list_event_attendees

List attendees for a specific event

list_event_types

List available event types/categories

list_events

List all community events

list_user_chapters

List chapters a specific user belongs to

search_chapters

Search for chapters by keyword

search_events

Search for events by keyword

Example Prompts for Bevy Community in LlamaIndex

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

"List all upcoming events in our community."

"Search for events matching 'SaaS'."

"Show the count of completed events this month."

Troubleshooting Bevy Community MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Bevy Community + LlamaIndex FAQ

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