Tencent START MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Tencent START as an MCP tool provider through the 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 Tencent START. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Tencent START?"
)
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 Tencent START MCP Server
Connect your AI agents to Tencent START Cloud Gaming (GS), the high-performance PaaS platform for cloud-native gaming. This MCP provides 11 tools to automate game instance locking, session creation, and scaling management.
LlamaIndex agents combine Tencent START tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through the 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
- Session Lifecycle — Lock workers, create server sessions, and stop games programmatically
- Resource Management — Monitor worker status and availability across different game IDs
- User Monitoring — Track concurrent users and worker assignments in real-time
- Capacity Scaling — Modify concurrency limits to dynamically adjust to player demand
The Tencent START MCP Server exposes 11 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 Tencent START to LlamaIndex via MCP
Follow these steps to integrate the Tencent START 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 11 tools from Tencent START
Why Use LlamaIndex with the Tencent START MCP Server
LlamaIndex provides unique advantages when paired with Tencent START through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Tencent START tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Tencent START tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Tencent START, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Tencent START tools were called, what data was returned, and how it influenced the final answer
Tencent START + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Tencent START MCP Server delivers measurable value.
Hybrid search: combine Tencent START real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Tencent START 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 Tencent START for fresh data
Analytical workflows: chain Tencent START queries with LlamaIndex's data connectors to build multi-source analytical reports
Tencent START MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Tencent START to LlamaIndex via MCP:
create_session
Initialize a cloud gaming session
get_capacity_limit
Check max concurrent user limit for a game
get_concurrent_user_info
Check current concurrency for a game
get_worker_info
Get worker info for a specific user
list_games
List games available on the Tencent GS platform
list_workers
List status of cloud gaming workers
modify_capacity_limit
Update max concurrent user limit for a game
stop_game
Ends a game session and releases the instance
stop_publish_stream
Stops the video stream for a specific user
stop_publish_stream_by_action
Stops the video stream using an explicit action code
try_lock_worker
Locks a cloud gaming instance for a specific user
Example Prompts for Tencent START in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Tencent START immediately.
"List all cloud games available in region 'ap-guangzhou'."
"Check the status of workers for game 'game_101'."
"Modify the concurrency limit for game 'game_202' to 100 users."
Troubleshooting Tencent START MCP Server with LlamaIndex
Common issues when connecting Tencent START to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTencent START + LlamaIndex FAQ
Common questions about integrating Tencent START 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 Tencent START 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 Tencent START to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.