
Connects Claude to Deutsche Bundesbank's official statistics through Pipeworx's gateway. The source doesn't list specific tools, but this gives you programmatic access to Germany's central bank data on monetary policy, financial markets, banking statistics, and economic indicators. Useful when you're building financial models, analyzing German economic trends, or need authoritative European financial data in your workflows. Part of Pipeworx's broader gateway that covers 250+ data sources, so you can either use this standalone endpoint or tap into the full gateway. Supports plain English queries through ask_pipeworx instead of calling tools directly.
Deutsche Bundesbank (Germany's central bank) statistics MCP.
Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.
| Tool | Description |
|---|---|
list_dataflows | List the available Bundesbank statistics dataflows (each is a series collection you can query with get_series). Returns SDMX 2.1 structure XML listing every dataflow id + name under agency BBK. Well-known flows: BBEX3 (exchange rates), BBK01 (legacy single time series), BBSIS (interest rates), BBBK1/BBBK2 (banking statistics), BBDB1 (balance of payments). Pass a flowRef to fetch just that one dataflow (includes its DataStructure reference). |
dataflow_structure | Get the data structure definition (DSD) for a dataflow: its dimensions and the valid codes for each, which you need to build a series key for get_series. Returns SDMX 2.1 structure XML. The DSD id differs from the dataflow id (e.g. dataflow BBEX3 uses DSD "BBK_ERX"). Pass the dataflow id (flowRef) and this tool resolves the DSD for you; the dimensions appear in in key order. Set withCodes=true (default) to inline the codelists (references=children). |
get_series | Pull observations for a Bundesbank series as SDMX-JSON. flowRef is the dataflow id (e.g. "BBEX3"); key is a dot-separated SDMX dimension filter in key order (e.g. "D.USD.EUR.BB.AC.000" = daily USD/EUR reference rate). Use dataflow_structure to discover the dimensions/codes for a flow. Leave a dimension empty to wildcard it (e.g. "D..EUR.BB.AC.000"). Filter by lastNObservations (most recent N) or a startPeriod/endPeriod date range (YYYY, YYYY-MM, or YYYY-MM-DD). |
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"bundesbank-de": {
"url": "https://gateway.pipeworx.io/bundesbank-de/mcp"
}
}
}
tools/list at https://gateway.pipeworx.io/bundesbank-de/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Both URLs reach the same gateway and the same 1476+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Bundesbank De data" })
The gateway picks the right tool and fills the arguments automatically.
MIT