How to Use the Leiting Games MCP in LlamaIndex

Index Leiting Games API data into your LlamaIndex RAG system for grounded, factual game development insights.

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Connect Leiting Games MCP to LlamaIndex

Create your Vinkius account to connect Leiting Games 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 Leiting Games with LlamaIndex

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Index live game publishing data

Use `list_games` to pull current titles into your vector store. Your RAG system now has an up-to-date catalog to answer questions about your published portfolio. Combine this with `get_game_status` to track specific deployments. You can query your knowledge base about the exact state of a build in the review pipeline.

Build a searchable compliance knowledge base

Feed `get_compliance_status` outputs into your index. Instead of scanning reports, ask your agent about specific policy adherence across all your games. Store `get_audit_logs` as context. Your agent retrieves past incidents or changes in status to provide grounded answers about your platform's history.

Query developer and partner intelligence

Index `get_developer_profile` and `get_partner_stats` to map your ecosystem. You can perform semantic searches to find high-performing partners or identify gaps in your dev relations. Use the retrieved data to generate internal summaries. Your LlamaIndex agent synthesizes these stats into actionable insights for your meetings.

Setup guide

Set up Leiting Games 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 Leiting Games 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 Leiting Games tools.",
)
response = await agent.run("List recent Leiting Games 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 Leiting Games. 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 Leiting Games MCP in LlamaIndex

You use the MCP client to fetch the tools and pass them to your tool spec. Once configured, LlamaIndex treats the API outputs as documents for your vector store.

No. By grounding your agent in live tool outputs, it relies on real-time API data. If a status isn't in the tool response, the agent knows it lacks the data.

Yes. The server provides the raw stats, and LlamaIndex indexes them. You can then ask natural language questions about your partner ecosystem.

The server manages the connection. Your index only contains the data you choose to store, and you control the access levels within your LlamaIndex application.

The server exposes game metadata, compliance logs, and partner statistics. These types are indexed as unstructured text or structured JSON snippets within your vector store.

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