Faceit MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Faceit as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Faceit. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Faceit?"
)
print(response)
asyncio.run(main())
* 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 Faceit MCP Server
Connect to Faceit and access the world's largest competitive gaming platform through natural conversation.
LlamaIndex agents combine Faceit tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Player Search — Find any player by nickname with Faceit level, ELO and game stats
- Player Stats — Get detailed CS2/Valorant stats including K/D, win rate, headshot %
- Match Details — View match results, scores and individual player performance
- Hub Info — Browse community hubs with matches, leaderboards and member info
- Tournaments — Search upcoming and ongoing tournaments by game and skill level
- Games Catalog — View all games supported on the Faceit platform
The Faceit MCP Server exposes 12 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 Faceit to LlamaIndex via MCP
Follow these steps to integrate the Faceit 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 12 tools from Faceit
Why Use LlamaIndex with the Faceit MCP Server
LlamaIndex provides unique advantages when paired with Faceit through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Faceit tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Faceit tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Faceit, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Faceit tools were called, what data was returned, and how it influenced the final answer
Faceit + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Faceit MCP Server delivers measurable value.
Hybrid search: combine Faceit real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Faceit 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 Faceit for fresh data
Analytical workflows: chain Faceit queries with LlamaIndex's data connectors to build multi-source analytical reports
Faceit MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Faceit to LlamaIndex via MCP:
get_games
Returns game IDs, names, icons and player counts. Get all supported games on Faceit
get_hub
Returns hub name, game, player count, rules, settings and organizer info. Get details for a specific Faceit hub
get_hub_leaderboard
Returns player rankings with nicknames, ELO, Faceit level and position. Get the leaderboard for a specific hub
get_hub_matches
Returns match IDs, teams, scores, status and timestamps. Filter by type: "all", "upcoming", "ongoing", "past". Get matches for a specific hub
get_match
Get details for a specific match
get_match_stats
Returns K/D/A, headshot %, K/R ratio, MVP rounds and other per-player performance metrics. Get player statistics for a specific match
get_player
Returns nickname, avatar, country, Faceit levels for all games, ELO ratings, member_since and game player IDs (Steam, Riot, etc.). Get detailed profile for a specific Faceit player
get_player_bans
Returns ban type, reason, date and duration. Get ban history for a player
get_player_history
Returns match IDs, results (win/loss), score, ELO change, date and game. Use game filter to get history for a specific game. Get match history for a player
get_player_stats
Returns matches played, win rate, K/D ratio, ELO, headshot percentage (CS2), average kills/deaths and current win streak. Get game-specific stats for a player
search_players
Returns player IDs, nicknames, avatars, Faceit levels, ELO ratings and game stats. Useful for finding any player on the platform. Search for Faceit players by nickname
search_tournaments
Returns tournament names, IDs, games, skill level requirements, start times, prize pools and registration status. Search for tournaments on Faceit
Example Prompts for Faceit in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Faceit immediately.
"Search for player s1mple on Faceit."
"Show me upcoming CS2 tournaments."
"Get the leaderboard for hub abc123."
Troubleshooting Faceit MCP Server with LlamaIndex
Common issues when connecting Faceit to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFaceit + LlamaIndex FAQ
Common questions about integrating Faceit MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Faceit with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Faceit to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.