How to Use the Criteo Retail Media API MCP in LlamaIndex

Q: Can I query historical Criteo Retail Media API reports using LlamaIndex RAG?

Yes, by indexing the outputs of getretailmediareport over time. LlamaIndex searches those vectorized reports to answer complex questions about past campaign trends.

Q: Does LlamaIndex support filtering tools from the Criteo Retail Media API?

Yes, you can use the allowedtools filter when initializing the client. This lets you restrict your LlamaIndex agent to read-only tools like listretailers if needed.

Index live Criteo ad data directly into LlamaIndex vector stores for ground-truth RAG.

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Connect Criteo Retail Media API MCP to LlamaIndex

Create your Vinkius account to connect Criteo Retail Media API 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 Criteo Retail Media API with LlamaIndex

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RAG-driven campaign analysis in LlamaIndex

This MCP Server connects your LlamaIndex pipelines directly to live campaign setups via `get_retail_campaign_details`. The tool retrieves raw campaign configurations and indexes them as document nodes in your vector store. Instead of guessing why a campaign is underperforming, your query engine searches past runs and compares them against current `list_retail_campaigns` outputs. This grounds your agent's answers in actual Criteo settings rather than training-data hallucinations.

Semantic search over retail product catalogs

The Criteo Retail Media API exposes your product listings through `list_account_products`, which LlamaIndex can ingest and vectorize. This lets your agent perform semantic queries over your active retail inventory. By combining this product data with `list_retailers`, your LlamaIndex agent maps out which items are active on which retail partner sites. You can ask natural language questions about SKU placement and get highly accurate, data-backed answers.

Vectorizing Criteo performance reports in LlamaIndex

This toolset allows your LlamaIndex agent to pull performance data using `get_retail_media_report` and store the structured results. The agent indexes these metrics to build a searchable history of ad performance. When you query the index about budget efficiency, LlamaIndex pulls the relevant report chunks along with active budgets from `list_retail_budgets`. Your agent synthesizes this data to explain exactly where spend is driving the highest return.

Setup guide

Set up Criteo Retail Media API 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 Criteo Retail Media API 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 Criteo Retail Media API tools.",
)
response = await agent.run("List recent Criteo Retail Media API 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 Criteo Retail Media. 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 Criteo Retail Media API MCP in LlamaIndex

You use the LlamaIndex MCP tool spec to load the tools and pass them to your LlamaIndex agent. The agent executes tools like `list_account_products` and writes the outputs directly to your index.

Yes, by indexing the outputs of `get_retail_media_report` over time. LlamaIndex searches those vectorized reports to answer complex questions about past campaign trends.

Yes, you can use the `allowed_tools` filter when initializing the client. This lets you restrict your LlamaIndex agent to read-only tools like `list_retailers` if needed.

Vinkius manages all Criteo authentication behind a single endpoint token. Your LlamaIndex code only needs to connect to the hosted MCP URL.

Your performance reports and retail budget data are processed in ephemeral V8 sandboxes. Vinkius never stores your Criteo API keys or the retrieved data payloads.

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