Odel
Bundesbank De

Bundesbank De

@pipeworx-ioTypeScriptMITUpdated 1w ago

Deutsche Bundesbank (Germany's central bank) statistics MCP.

Server endpointStreamable HTTPNo authProbed

This is the third-party server itself — Odel doesn't run it. Hitting this URL directly talks straight to the upstream server with no auth or proxying. Connect through Odel to front it with managed auth.

mcp-bundesbank-de

Deutsche Bundesbank (Germany's central bank) statistics MCP.

Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.

Tools

ToolDescription
list_dataflowsList 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_structureGet 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_seriesPull 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).

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "bundesbank-de": {
      "url": "https://gateway.pipeworx.io/bundesbank-de/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/bundesbank-de/mcp returns the tools in the table above plus the shared Pipeworx meta-toolsask_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.

Using with ask_pipeworx

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.

More

License

MIT