SDMX (Statistical Data and Metadata eXchange) is an international standard for exchanging statistical data. The ECB, Eurostat, IMF, World Bank, and other institutions use SDMX for their APIs. Data is organized in dataflows → dimensions → observations.

Do I need an API key to access this data?

No, the ECB Statistical Data Warehouse public API is completely open and free. There is no authentication or token required to fetch any of the datasets provided.

How often is the statistical data updated?

The data is updated in real-time according to the ECB's official publishing schedule. Daily exchange rates typically update around 16:00 CET.

ECB Discovery — Universal Statistical Data Access MCP Server for LlamaIndex 2 tools — connect in under 2 minutes

Name: ECB Discovery — Universal Statistical Data Access
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 2 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ECB Discovery — Universal Statistical Data Access as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to ECB Discovery — Universal Statistical Data Access. "
            "You have 2 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in ECB Discovery — Universal Statistical Data Access?"
    )
    print(response)

asyncio.run(main())

ECB Discovery — Universal Statistical Data Access

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About ECB Discovery — Universal Statistical Data Access MCP Server

Universal access to all ECB data.

LlamaIndex agents combine ECB Discovery — Universal Statistical Data Access tool responses with indexed documents for comprehensive, grounded answers. Connect 2 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

2 Tools

List Dataflows — Complete catalog of ECB datasets
Query Data — Any dataflow with custom SDMX keys

The ECB Discovery — Universal Statistical Data Access MCP Server exposes 2 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect ECB Discovery — Universal Statistical Data Access to LlamaIndex via MCP

Follow these steps to integrate the ECB Discovery — Universal Statistical Data Access MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 2 tools from ECB Discovery — Universal Statistical Data Access

Why Use LlamaIndex with the ECB Discovery — Universal Statistical Data Access MCP Server

LlamaIndex provides unique advantages when paired with ECB Discovery — Universal Statistical Data Access through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine ECB Discovery — Universal Statistical Data Access tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain ECB Discovery — Universal Statistical Data Access tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query ECB Discovery — Universal Statistical Data Access, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what ECB Discovery — Universal Statistical Data Access tools were called, what data was returned, and how it influenced the final answer

ECB Discovery — Universal Statistical Data Access + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the ECB Discovery — Universal Statistical Data Access MCP Server delivers measurable value.

Hybrid search: combine ECB Discovery — Universal Statistical Data Access real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query ECB Discovery — Universal Statistical Data Access to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying ECB Discovery — Universal Statistical Data Access for fresh data

Analytical workflows: chain ECB Discovery — Universal Statistical Data Access queries with LlamaIndex's data connectors to build multi-source analytical reports

ECB Discovery — Universal Statistical Data Access MCP Tools for LlamaIndex (2)

These 2 tools become available when you connect ECB Discovery — Universal Statistical Data Access to LlamaIndex via MCP:

list_dataflows

Each dataflow has a code (e.g., EXR, FM, BSI) and description. Use these codes with the generic query tool to access any ECB data. List all available ECB statistical dataflows

query_ecb_data

Provide the dataflow code (EXR, FM, BSI, YC, MIR, BKN, etc.) and a SDMX series key. Use list_dataflows to find dataflow codes. Example: dataflow=EXR, key=D.USD.EUR.SP00.A for daily USD/EUR rate. Query any ECB dataset with a SDMX series key — universal access

Example Prompts for ECB Discovery — Universal Statistical Data Access in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with ECB Discovery — Universal Statistical Data Access immediately.

"What ECB datasets are available?"

"Query the Balance Sheet Items (BSI) dataset."

"Extract the latest MFI Interest Rates."

Troubleshooting ECB Discovery — Universal Statistical Data Access MCP Server with LlamaIndex

Common issues when connecting ECB Discovery — Universal Statistical Data Access to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

ECB Discovery — Universal Statistical Data Access + LlamaIndex FAQ

Common questions about integrating ECB Discovery — Universal Statistical Data Access MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query ECB Discovery — Universal Statistical Data Access tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.