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

Q: Can I filter Marketplacer (Enterprise Marketplace Platform) data in LlamaIndex?

Yes, use the allowedtools filter during client setup. This limits which functions the agent can execute, keeping your index focused on specific data subsets.

Index your Marketplacer (Enterprise Marketplace Platform) data into LlamaIndex for semantic search and grounded answers.

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Connect Marketplacer (Enterprise Marketplace Platform) MCP to LlamaIndex

Create your Vinkius account to connect Marketplacer (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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Setup Marketplacer (Enterprise Marketplace Platform) with LlamaIndex

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Turn your marketplace data into a searchable knowledge base. By indexing results from `list_adverts`, your agent can answer questions about product availability using actual platform records. This prevents the agent from guessing. It anchors every response in the live data pulled directly from your marketplace instance.

Semantic search over order history

Use `list_invoices` to populate your index with historical order data. You can then query your knowledge base to find patterns in sales or identify missing shipment info. This makes your historical data queryable in plain English. Your agent retrieves the relevant node IDs and presents the info clearly.

Unified knowledge retrieval in LlamaIndex

Combine API data with your private documents. The agent pulls relevant info using `list_categories` and merges it with your internal manuals to give comprehensive support answers. Everything is indexed together. You get a single source of truth that stays updated with the latest changes from the Marketplacer (Enterprise Marketplace Platform).

Setup guide

Set up Marketplacer (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

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

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Common questions about Marketplacer (Enterprise Marketplace Platform) MCP in LlamaIndex

The MCP tool spec retrieves the raw data and passes it to your vector store. LlamaIndex then converts this data into embeddings for semantic retrieval.

Yes, use the allowed_tools filter during client setup. This limits which functions the agent can execute, keeping your index focused on specific data subsets.

Your index is local to your environment. The server uses ephemeral transport, and only the data you explicitly fetch and index is stored.

Re-run the tool collection process whenever your marketplace data changes. LlamaIndex will refresh the vector store with the latest records retrieved from the server.

The agent catches the exception during the tool call. You should configure your LlamaIndex error handling to log these failures without crashing your search pipeline.

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