How to Use the Eurostat Discovery — Dataset Catalog Explorer MCP in LlamaIndex

Q: What's the process for connecting Eurostat Discovery — Dataset Catalog Explorer to my LlamaIndex agent?

It's straightforward. Use the McpToolSpec to wrap the client, which converts the server's tools into a format LlamaIndex can use. Then, just pass the tool list to your agent.

Q: Is it possible to filter which Eurostat datasets my agent can access with Eurostat Discovery — Dataset Catalog Explorer and LlamaIndex?

Yes. The McpToolSpec in LlamaIndex supports an allowedtools filter. You can explicitly define which of the three tools—searchdatasets, getdatasetmetadata, or getdataset—the agent is permitted to call.

Index live Eurostat data into a queryable knowledge base with LlamaIndex. Ground your RAG agent in facts, not just training data.

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Connect Eurostat Discovery — Dataset Catalog Explorer MCP to LlamaIndex

Create your Vinkius account to connect Eurostat Discovery — Dataset Catalog Explorer 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 Eurostat Discovery — Dataset Catalog Explorer with LlamaIndex

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Turn EU Stats into a Knowledge Base

Don't just fetch data—index it. When your agent uses `search_datasets` or pulls data with `get_dataset`, LlamaIndex can automatically embed and store the results in a vector index. It's a way to build a memory of past discoveries. This means your agent gets smarter over time. It learns the structure of the Eurostat catalog and can retrieve previously fetched data instantly, without hitting the API again.

Ground Answers in Live API Data

Build a RAG application that answers questions with up-to-the-minute European statistics. When a user asks about current trade balances, your agent calls `get_dataset` to get the latest numbers directly from the source. This is how you fight hallucination. The agent's answers are backed by verifiable data from the Eurostat API, not just patterns from its training set. You can even configure it to cite the dataset code it used.

Query Past Sessions with This MCP Server

The output from this MCP Server becomes a persistent asset. Last month you pulled employment data; today you can ask your agent a semantic question about it. LlamaIndex finds the relevant, indexed results from your past queries. This turns one-off API calls into a searchable history. You're not just executing tool calls, you're building an institutional knowledge base grounded in real statistical data.

Setup guide

Set up Eurostat Discovery — Dataset Catalog Explorer 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 Eurostat Discovery — Dataset Catalog Explorer 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 Eurostat Discovery — Dataset Catalog Explorer tools.",
)
response = await agent.run("List recent Eurostat Discovery — Dataset Catalog Explorer 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 Eurostat. 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 Eurostat Discovery — Dataset Catalog Explorer MCP in LlamaIndex

It provides the "R" in RAG—Retrieval. Your agent retrieves live European Union statistics using the `get_dataset` tool, then uses that data as context to generate an accurate, augmented answer.

Yes, that's a core LlamaIndex pattern. You can configure a data agent to automatically index the JSON output from any tool call, including `get_dataset`, making the raw statistical data searchable.

It's straightforward. Use the `McpToolSpec` to wrap the client, which converts the server's tools into a format LlamaIndex can use. Then, just pass the tool list to your agent.

Yes. The `McpToolSpec` in LlamaIndex supports an `allowed_tools` filter. You can explicitly define which of the three tools—`search_datasets`, `get_dataset_metadata`, or `get_dataset`—the agent is permitted to call.

The Vinkius MCP server itself stores nothing; it processes your requests for European Union statistical data and returns the result. LlamaIndex, however, is designed to index data. It's your responsibility to secure the vector database where you choose to store the indexed results.

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