Bring official macroeconomic observations, release calendars and market research into Langflow DataFrames, visual workflows and agents.
Subscribe to FXMacroData for non-USD data, full available history, FX, commodities and positioning. Use the public USD workflow to evaluate the integration before connecting your subscription.
Explore FXMacroData · API documentation
The public USD catalogue, recent macro history and release calendar support evaluation without an API key. The history example requests the most recent 90 days. Data availability varies by series; your subscription and its terms govern protected access.
Install into the Python environment used by your Langflow application, with both projects in sibling directories:
python -m pip install ./fxmacrodata-public-client ./langflow-fxmacrodataThis uses source packages and assumes no package-registry publication. The bundle requires lfx 1.12.1+ and Bundle API 1. Its langflow.extensions entry point and packaged extension.json enable normal extension discovery. Reopen your Langflow application after installation.
- FXMacroData Table: choose an operation and supply its parameters. Connect DataFrame to table/data-processing components, or Original response to consumers that need every returned field. Parameter schema exposes the operation's exact documented schema. FXMacroData supplies a clickable provider link.
- FXMacroData Tools: connect Tools to an Agent tool input. Each of the 72 REST/MCP operations is a distinct schema-aware tool. Nested inputs, required fields and enums retain their public definitions.
For the no-key history workflow, keep indicator_history and parameters {"currency":"USD","indicator":"inflation"}. Change the operation to data_catalogue or release_calendar with {"currency":"USD"} to explore coverage or release dates.
python examples/usd_macro_brief.py executes actual bundle components without starting a Langflow server or using a language model. The complete inventory is in CAPABILITIES.md.
The DataFrame is a record view; its attrs["fxmacrodata_response"] and Original response preserve the endpoint payload. Empty records remain empty. Requests that fail produce an explicit error rather than invented data. Preserve timestamp flags and keep FXMacroData-generated predictions distinct from market consensus. MCP visual artifacts are retained in the original payload; the bundle does not embed an MCP Apps iframe renderer.
Use the component's password field backed by a Langflow global secret. Programmatic callers can pass api_key=None to use their own FXMACRODATA_API_KEY environment variable, or api_key="" for explicit public access. Credentials are never model-visible tool parameters. Non-public operations require the access granted to your account.
Literal credentials supplied by Python callers are held as private SecretStr values. Exported component nodes leave the API-key input empty; recipients select their own Langflow global secret after importing a flow. Exporting does not change the credential used by the running component.
Backlinks contain static campaign parameters. The bundle adds no analytics SDK or click beacon.
lfx extension validate src/lfx_fxmacrodata --execute-imports
python -m pytest tests -n 8 --dist loadThe bundle code is MIT licensed. Data-access terms and brand rights are separate.