How to Use the Ad4Game MCP in LlamaIndex

Q: How do I index Ad4Game data using LlamaIndex?

Install llama-index-tools-mcp and instantiate the Basic MCP client. Wrap it in McpToolSpec and convert it to tools for your FunctionAgent to start indexing your game marketing data.

Q: Can LlamaIndex search through old Ad4Game creatives?

Yes, once your agent calls getcreatives, you can index the asset metadata into a vector store. This allows LlamaIndex to perform semantic search over past creatives to find matching visual assets.

Q: How does LlamaIndex prevent hallucinated payouts with Ad4Game?

The agent uses getofferdetails to fetch live data directly from the API. LlamaIndex reads this output as a source document, ensuring the agent's responses are grounded in actual ad terms.

Q: Does the LlamaIndex MCP Server integration support tool filtering?

Yes, you can use the allowedtools filter when setting up the client. This restricts your LlamaIndex agent to specific actions like listoffers if you want to prevent it from fetching creatives.

Build a searchable knowledge base of game ad offers and creatives by indexing Ad4Game data directly in LlamaIndex.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Ad4Game MCP to LlamaIndex

Create your Vinkius account to connect Ad4Game 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.

GDPR Free for Subscribers

Setup Ad4Game with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Semantic search over game offers in LlamaIndex

When your query agent runs `list_offers`, the output is indexed directly into your vector store, allowing you to run semantic search queries over your entire game campaign catalog. LlamaIndex doesn't just call the tools blindly. Instead of exact keyword matches, your agent finds relevant campaigns based on concept or target audience. It queries the vector database to find the best match, then uses `get_offer_details` to retrieve the current payout.

RAG-driven creative matching via MCP Server

Your LlamaIndex agent uses `get_creatives` to pull visual assets, stores their metadata in a queryable index, and retrieves them using natural language. This setup stops you from guessing which banner fits your blog post or social copy. This workflow lets you build retrieval-augmented generation pipelines that ground your marketing copy in actual, active creative assets. Your agent will only write copy that matches the visual style of your running game ads.

Grounded decision making with live ad inventory

By calling `get_offer_details` through the LlamaIndex framework, the agent bases its recommendations on real-time API data retrieved straight from the server. This prevents hallucinations about campaign payouts and rules. The framework treats the live tool outputs as temporary document nodes. This ensures that any strategy your agent proposes is strictly constrained by the actual terms of the active gaming offers.

Setup guide

Set up Ad4Game 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 Ad4Game 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 Ad4Game tools.",
)
response = await agent.run("List recent Ad4Game data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ad4Game. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Ad4Game now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Ad4Game MCP in LlamaIndex

Install `llama-index-tools-mcp` and instantiate the Basic MCP client. Wrap it in `McpToolSpec` and convert it to tools for your `FunctionAgent` to start indexing your game marketing data.

Yes, once your agent calls `get_creatives`, you can index the asset metadata into a vector store. This allows LlamaIndex to perform semantic search over past creatives to find matching visual assets.

The agent uses `get_offer_details` to fetch live data directly from the API. LlamaIndex reads this output as a source document, ensuring the agent's responses are grounded in actual ad terms.

Yes, you can use the allowed_tools filter when setting up the client. This restricts your LlamaIndex agent to specific actions like `list_offers` if you want to prevent it from fetching creatives.

Vinkius runs the server in an isolated, zero-trust V8 sandbox. Your ad inventory data and offer details are processed ephemerally, ensuring no sensitive marketing metrics are stored or leaked outside your active LlamaIndex session.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript