How to Use the BattleMetrics MCP in LlamaIndex

Q: Can LlamaIndex filter which BattleMetrics tools are available?

You can restrict access using the allowedtools parameter. If you only want your app to read public data, include listgames and getgame while excluding administrative actions like getban.

Q: How do I paginate through large server lists?

The listservers and searchservers tools accept a pagenumber argument. Your agent will iteratively call the tool, incrementing the page integer, and index the returned batches until it hits the end of the results.

Index BattleMetrics player histories into LlamaIndex to query live gaming data alongside your internal documents.

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Connect BattleMetrics MCP to LlamaIndex

Create your Vinkius account to connect BattleMetrics 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 BattleMetrics with LlamaIndex

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Ground RAG Apps in Live Server Data

Building a knowledge base around game communities requires actual numbers, not guesses. Your LlamaIndex application calls `get_server` to pull real-time player counts, IP addresses, and map rotations. It takes that JSON payload and embeds it directly into your vector store. Users can then query the index to ask about current server status. Instead of hallucinating a response, the engine retrieves the exact node containing the `get_server_leaderboard` output. You get answers backed by hard playtime durations and specific player IDs.

Index BattleMetrics Player Sessions

Tracking user behavior across wipes or seasons generates massive amounts of data. You use the `get_player_sessions` tool to extract join times, leave times, and total session lengths for specific users. LlamaIndex chunks this timeline data and stores it for semantic search. When a community manager asks if a player was active during a specific incident, the RAG pipeline searches the embedded session history. It cross-references the timestamps with server logs you have already indexed, providing a complete picture of who was online.

Query Historical Population Trends via MCP Server

Analyzing how updates affect player retention means looking at historical arrays. Your setup triggers `get_server_player_count_history` using specific ISO 8601 date ranges. The model processes the time-series data and adds it to your document index. You can then ask your interface to compare last month's peak hours against this week's numbers. LlamaIndex retrieves the embedded trend data and synthesizes a factual summary. The MCP connection ensures your vector store always has a path to fresh API data.

Setup guide

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

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

Run pip install llama-index-tools-mcp in your environment. Initialize a BasicMCPClient with your Vinkius endpoint, then wrap it in McpToolSpec. Call to_tool_list_async() and hand those tools to your FunctionAgent.

You can restrict access using the allowed_tools parameter. If you only want your app to read public data, include list_games and get_game while excluding administrative actions like get_ban.

The framework embeds the tool outputs into your configured vector store. This allows your application to perform semantic searches over historical API responses long after the initial query finishes.

The list_servers and search_servers tools accept a page_number argument. Your agent will iteratively call the tool, incrementing the page integer, and index the returned batches until it hits the end of the results.

Pulling moderation logs exposes administrator names and internal ban reasons. Vinkius routes these requests through an ephemeral zero-trust environment. The server instance spins up just for your query and terminates immediately, leaving zero persistent storage behind.

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