Implementation
Step-by-step setup guides for authentication, endpoint usage, and production integrations.
Start with a workflow
These guides take you from one authenticated request to scheduling, forecast evaluation, real-time updates, and a repeatable macro model.
Add a free, live economic calendar to a static site on Netlify, Vercel, GitHub Pages, or Cloudflare Pages: paste the FXMacroData snippet, deploy, allow it in your Content-Security-Policy, and load it once in React or Next.js.
Add a free, live economic calendar to a Wix page: paste the FXMacroData snippet into an Embed HTML element, size it so the attribution link stays visible, set the mobile layout, and publish.
Most macro backtests fail in the data, not the strategy: revised consensus columns, reference-period timestamps, and silently updated actuals all leak the future into the past. This guide walks through the point-in-time acceptance rule, how FXMacroData enforces it structurally, honest pre-release forecast coverage by event family, and a full forecast-to-actual join in Python.
Use Thinking Machines Inkling with FXMacroData to turn current releases, event timing, and FX context into evidence-backed trading research—MCP first, REST where an application needs direct control.
Use Meta Muse Spark 1.1 with FXMacroData as a disciplined macro-research workflow: connect the MCP server for tool use, reserve REST for repeatable checks, and produce evidence-backed FX trade-prep packets for human review.
Use Kimi K3 with FXMacroData MCP first to turn release calendars, announcement history, FX context, and scenario prompts into evidence-backed trading research.
Use FXMacroData through Fast Trade by building pair-level macro context, attaching it to backtest research, and exposing it through the fast-trade MCP server.
Use FXMacroData through Roboquant by fetching release-calendar rows, filtering top-tier macro events, and wrapping a strategy with a calendar blackout guardrail.
Use FXMacroData through Pinkfish by fetching FX reference rates into a Pinkfish-ready OHLC dataframe, caching the data, and running repeatable daily FX research tests.
Use Vercel AI SDK with FXMacroData to build typed, evidence-first FX research tools with structured outputs and reviewable model workflows.
Use Amazon Bedrock AgentCore with FXMacroData to ground FX research agents in current macro evidence while keeping execution outside the model path.
Use Hugging Face Transformers with FXMacroData to turn current macro evidence into reviewable AI trading research without putting execution decisions in the model path.
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We welcome article submissions and ideas for the FXMacroData library. Send your pitch or draft to info@fxmacrodata.com.
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