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How to Use the MobyGames MCP in LlamaIndex

Index MobyGames metadata into LlamaIndex vector stores to query game history without hallucinations.

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LlamaIndex

Connect MobyGames MCP to LlamaIndex

Create your Vinkius account to connect MobyGames 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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Build a searchable MobyGames index with LlamaIndex

LlamaIndex goes beyond simple API calls by turning MobyGames metadata into searchable documents. Your LlamaIndex agent calls `get_game_by_id` and `get_reviews`, then indexes that raw text directly into your vector store. The MCP integration grounds your LlamaIndex application in real MobyGames data. Instead of guessing release dates or review scores, the agent queries your local index first, only calling `search_games` when it needs to fetch fresh titles.

Query developer histories using this MCP Server

Combine MobyGames developer profiles with game credits to build a unified LlamaIndex knowledge graph. The system calls `get_developers` and `get_game_credits` to pull raw biographical and professional data, which LlamaIndex then indexes as node relationships. This means you can ask LlamaIndex complex questions about which programmers worked on specific platforms. Your query engine resolves the relationships locally, using `get_platforms` to verify console IDs before retrieving new MobyGames records.

Filter indexed MobyGames attributes dynamically

Keep your LlamaIndex vector index clean by resolving categories before you ingest MobyGames data. Your LlamaIndex pipeline calls `get_attributes` and `get_genres` to categorize games like open-world or free-to-play before they hit your vector store. By structuring your MobyGames metadata first, your LlamaIndex semantic searches become incredibly precise. You can filter your vector queries by specific genre IDs, ensuring your RAG application only returns highly relevant game profiles.

Setup guide

Set up MobyGames MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.

  2. 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. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all MobyGames MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 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 MobyGames tools.",
)
response = await agent.run("List recent MobyGames data")

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

Install `llama-index-tools-mcp` to connect your client to the MCP Server. Convert the client to tools using the MCP Server and pass them to your LlamaIndex `FunctionAgent`.
Yes, your LlamaIndex pipeline can call `get_reviews` for a specific game ID and index those review texts directly into a vector store for semantic search.
Use LlamaIndex's MCP tool specification to force the agent to call `get_game_by_id` for factual data, ensuring the response is grounded in actual database records.
Yes, you can apply an `allowed_tools` filter during LlamaIndex setup to restrict the agent to specific endpoints like `search_games` and `get_platforms`.
The server only processes game profiles, developer names, and platform IDs. Vinkius hosts the server in a secure sandbox, ensuring your search queries and API keys remain private.

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