ECB Discovery MCP. Query Eurozone economic data directly from the ECB.
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ECB Discovery — Universal Statistical Data Access lets you query the entire European Central Bank (ECB) statistical catalog. It lets your AI client browse all available dataflows—from exchange rates and monetary aggregates to banking supervision and payment statistics—and query any dataset using specific SDMX keys.
You get universal access to Eurozone economic data directly through your agent.
What your AI agents can do
List dataflows
Retrieves the complete list of available ECB statistical dataflows and their corresponding codes.
Query ecb data
Queries any ECB dataset by supplying a dataflow code and a full SDMX series key.
Runs list_dataflows to provide a full catalog of all available statistical dataflows and their codes (e.g., EXR, FM, BSI).
Uses query_ecb_data to retrieve time series data from any listed dataflow using a precise SDMX series key.
Retrieves data on M1, M2, and M3 monetary aggregates via the BSI dataflow.
Pulls historical exchange rates (e.g., USD/EUR) using the EXR dataflow.
Queries payment volume and value data using the STP dataflow.
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ECB Discovery: 2 Tools for Economic Data Queries
Use these tools to browse the full ECB statistical catalog and pull specific, structured time series data from any available dataflow.
019d758blist dataflows
Retrieves the complete list of available ECB statistical dataflows and their corresponding codes.
019d758bquery ecb data
Queries any ECB dataset by supplying a dataflow code and a full SDMX series key.
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What you can do with this MCP connector
ECB Discovery — Universal Statistical Data Access lets your AI client query the entire European Central Bank (ECB) statistical catalog. You get universal access to Eurozone economic data directly through your agent. You'll use list_dataflows to pull a complete list of all available ECB statistical dataflows and their codes, like EXR, FM, or BSI.
You can then use query_ecb_data to pull time series data from any listed dataflow by supplying a dataflow code and a full SDMX series key. You can analyze payment statistics by querying the STP dataflow for payment volume and value data. You'll pull historical exchange rates, like USD/EUR, using the EXR dataflow.
You can get data on M1, M2, and M3 monetary aggregates by accessing the BSI dataflow. You'll also get data on banking supervision and payment statistics. You can query any dataset using a precise SDMX series key.
How ECB Discovery MCP Works
- 1 Run
list_dataflowsto get the specific dataflow code (e.g.,EXR) needed for your query. You can't query data without knowing the correct code. - 2 Provide the dataflow code and the exact SDMX series key (e.g.,
D.USD.EUR.SP00.A) to thequery_ecb_datatool. The key tells the server exactly which data point you want. - 3 Your agent receives the raw time series data, which includes the requested metric, time period, and the source dataflow, ready for analysis.
The bottom line is that you use list_dataflows to find the catalog, and query_ecb_data to pull the specific, structured data you need.
Who Is ECB Discovery MCP For?
The quantitative analyst who needs to verify a specific historical economic metric without spending hours navigating the ECB website. It's for the research economist who needs to quickly compare monetary aggregates across different time periods, or the compliance officer who needs to pull specific financial data for a report. You stop guessing and start querying.
Uses query_ecb_data to pull specific time series data for modeling, such as comparing M1 to M2 growth rates over a decade.
Runs list_dataflows first, then query_ecb_data to gather broad datasets—like payment statistics or yield curves—for report writing and trend analysis.
Checks historical data on banking supervision or financial market items using the appropriate dataflows to assess systemic risk.
What Changes When You Connect
- Need to check a specific exchange rate? Instead of visiting the ECB site and clicking through menus, just use
query_ecb_datawith theEXRdataflow and the key. You get the raw USD/EUR rate in seconds. - Comparing monetary aggregates (M1, M2, M3) used to be a nightmare of manual downloads. Now, you run
query_ecb_dataagainst theBSIdataflow, and your agent pulls the structured comparison instantly. - The
list_dataflowstool gives you the master list. It saves you from having to guess which data code—likeSTPorFM—you need before starting a query. - You eliminate manual data extraction. Instead of downloading CSVs and pasting them into Excel, your agent pulls the structured time series data directly into your workflow.
- It handles the complexity of SDMX keys. You just need the dataflow code and the key; the tool handles the connection to the right part of the massive ECB database.
Real-World Use Cases
Analyzing M1/M2/M3 trends over time
The analyst needs to track the relationship between M1, M2, and M3. They first use list_dataflows to confirm the BSI code. Then, they run query_ecb_data with the correct key to get a time series comparison, solving the problem in minutes instead of hours of manual data gathering.
Finding the correct data code for a new metric
A researcher hears about 'Payment Statistics' but doesn't know the code. They run list_dataflows. The tool returns STP. They then use query_ecb_data with STP to pull the required data, overcoming the initial discovery hurdle.
Comparing today's exchange rate to last year's
A portfolio manager needs a historical comparison of USD/EUR. They use list_dataflows to confirm EXR. They then call query_ecb_data with the full key and date range, getting the exact historical data point immediately for a market report.
Building a comprehensive financial report
An economist needs to pull data from three different areas: exchange rates, balance sheets, and yield curves. They use list_dataflows to find EXR, BSI, and YC. They then chain three separate query_ecb_data calls to gather all the necessary data points for a single, unified report.
The Tradeoffs
Manual website navigation
Jumping to the ECB website, clicking through the 'Statistics' section, finding the 'Monetary Aggregates' tab, and finally downloading the required CSV file. This takes 20-30 minutes of clicks and copy-pasting.
→
First, run list_dataflows to confirm the BSI code. Then, use query_ecb_data with the specific key. Your agent handles the entire process in one go, skipping all the clicks.
Guessing the dataflow code
Trying to query data without knowing the correct dataflow code, leading to an API failure or a generic error message. You waste time debugging the tool, not the data.
→
Always start by running list_dataflows. This gives you the authoritative code list, ensuring your subsequent calls to query_ecb_data hit the right data source.
Using generic data APIs
Relying on a general-purpose data API that might not support the complex SDMX standards or specific Eurozone keys required by the ECB.
→
Use query_ecb_data. It is built specifically for the ECB's SDMX standard, guaranteeing that the complex keys and data structures work correctly every time.
When It Fits, When It Doesn't
Use this if your job requires accessing highly standardized, structured time series data directly from the European Central Bank's official catalog. If you need to compare M1/M2/M3 across multiple years, or pull daily exchange rates (EXR), this is the tool. Don't use it if you need data that hasn't been published to the ECB's official statistics platform, or if you are looking for qualitative, narrative insights (e.g., 'Why did inflation spike in Q1?'). For narrative analysis, you need a text model; for structured data, you use query_ecb_data after confirming the dataflow with list_dataflows.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by European Central Bank. 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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 2 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through the ECB website for one data point shouldn't take an hour.
Today, pulling a single metric—say, the latest M2 aggregate—means navigating the ECB data portal. You're clicking through dozens of tabs, filtering by date ranges, and often downloading a massive CSV just to copy one number. It's tedious, and the chances of picking the wrong dataset are high.
With this MCP Server, you tell your agent what you need. It runs `list_dataflows` to find the right code, then uses `query_ecb_data` to pull the specific time series data. You get the number, structured and ready, in seconds.
ECB Discovery: Get Structured Data with `query_ecb_data`
Manual processes force you to manage multiple endpoints: the main catalog page, the specific data page, and the download mechanism. You have to manually track the dataflow code and the SDMX key.
Now, you just define the dataflow and the key. The system handles the connection and the data retrieval. It's direct, single-call access to the source data.
Common Questions About ECB Discovery MCP
How do I start using the `list_dataflows` tool? +
Run list_dataflows with no arguments. It provides a table listing all available ECB dataflow codes (like EXR, BSI, STP) and their descriptions. This is your starting point for any query.
What is the full process for using `query_ecb_data`? +
You must first find the dataflow code using list_dataflows. Then, call query_ecb_data, passing the dataflow code and the exact SDMX series key. The key is critical.
Can I query data that isn't listed in `list_dataflows`? +
No. The list_dataflows tool provides the definitive, current catalog. If it's not listed, the dataflow code doesn't exist in the server.
What dataflows are available for monetary aggregates? +
The BSI dataflow handles Balance Sheet Items, which include monetary aggregates (M1, M2, M3). Use this code in list_dataflows to confirm, then use it in query_ecb_data.
How do I use `query_ecb_data` if I don't know the SDMX series key? +
You must first use the list_dataflows tool to find the relevant dataflow code. Once you have the code (like EXR or BSI), you can then refine your search for specific series keys by checking the ECB's documentation.
What happens if I provide an invalid dataflow code to `query_ecb_data`? +
The system returns a clear error message identifying the invalid dataflow code. You simply need to re-run the query using the correct code found via list_dataflows.
Does `list_dataflows` provide metadata about the data, or just the code? +
It provides both the code and a description for each dataset. This helps you understand the scope of the dataflow (e.g., Exchange Rates or Financial Markets) before you attempt a query.
Can `query_ecb_data` handle different time periods, like quarterly vs. annual data? +
Yes. The SDMX key structure allows you to specify the required time interval. Simply include the appropriate frequency or year range within your series key parameter.
What is SDMX? +
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.
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