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How to Use the Mirakl (Enterprise Marketplace Platform) MCP in LlamaIndex

Index your Mirakl seller configurations and order histories directly into LlamaIndex vector stores.

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LlamaIndex

Connect Mirakl (Enterprise Marketplace Platform) MCP to LlamaIndex

Create your Vinkius account to connect Mirakl (Enterprise Marketplace Platform) 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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Index Global Offers for Semantic Search

The `list_offers` tool extracts live pricing and inventory data from your marketplace to build a searchable knowledge index. This feeds current merchant offer data straight into your LlamaIndex pipelines. Your agent searches this index to find specific pricing trends. By combining this with `get_offer`, your RAG application grounds its answers in actual merchant limits and live pricing data.

Retrieve Structured Invoices and Messages

The `list_invoices` tool fetches accounting data to help you build financial knowledge bases in LlamaIndex. This removes the need to manually export billing documents. You can also call `list_messages` to index internal merchant communications. This lets your query engine answer questions about seller disputes using actual historical chat logs.

Build RAG Pipelines with this MCP Server

The `list_shops` tool retrieves active merchant profiles to help you build a searchable repository of seller configurations with this MCP Server. Your LlamaIndex application uses this directory to answer complex partner queries. When a query demands deep configuration details, the agent invokes `get_shop` to fetch the specific merchant rules. This guarantees your RAG system uses factual configuration parameters instead of guessing.

Setup guide

Set up Mirakl (Enterprise Marketplace Platform) 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 Mirakl (Enterprise Marketplace Platform) 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 Mirakl (Enterprise Marketplace Platform) tools.",
)
response = await agent.run("List recent Mirakl (Enterprise Marketplace Platform) data")

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

Use llama-index-tools-mcp to initialize the client and convert the marketplace tools into a LlamaIndex tool spec. This exposes endpoints like list_products directly to your query engines.
Yes. By calling get_order, your agent pulls real-time transaction data to answer customer support queries with precise, verified shipping and billing facts.
You can schedule pipelines that call list_categories and list_products to continuously refresh your vector database with the latest marketplace catalog structure.
You can pass an allowed tools filter during initialization. This prevents your agent from calling sensitive tools like list_invoices while keeping catalog tools active.
Your seller shop configurations and financial invoices are processed entirely in memory within the Vinkius sandbox. No external parties can view your credentials or the payload of your get_shop calls.

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