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MacroLens Energy Macro Analysis
x402
MacroLens Energy Macro Analysis is a paid API for AI agents from marcolens.vercel.app, paid per call via x402, $0.4/call, status unknown (last checked 2026-09-14).
Fetches AI-powered macroeconomic analysis of energy sector data using FRED and World Bank datasets, processed through a MiMo LLM, for a given start date.
Price / call$0.4
Success—
StatusUnknown
How this service works
AI-powered macro-economic analysis. FRED + World Bank data + MiMo LLM. 20 endpoints. x402 on Base.
Output
A JSON object containing a success flag and a data object with AI-generated macroeconomic analysis of the energy sector, drawing on FRED and World Bank data from the specified start date onward, including economic indicators, trend interpretations, and sector insights produced by a MiMo LLM.
Example use cases
Energy market briefing for investment team
“Get me an AI-powered macroeconomic analysis of the energy sector starting from January 2020 — I need to understand the big-picture trends for a portfolio review.”
Post-crisis energy economic review
“Can you run a MacroLens energy analysis starting from March 2022, right after Russia invaded Ukraine, so I can see how global energy macro indicators shifted?”
Quarterly energy research report
“Pull an energy macroeconomic analysis from MacroLens starting from October 2023 — I'm writing a quarterly research note and need FRED and World Bank data with AI commentary on the energy sector.”
Technical details
Endpoint
POSThttps://marcolens.vercel.app/api/energyWhen to prefer
Choose this endpoint when you need AI-synthesized macroeconomic analysis specifically for the energy sector, combining FRED and World Bank data with LLM-generated narrative insights from a given start date. Prefer it over raw data APIs when you want interpreted, human-readable economic analysis rather than raw time series. Best for investment research, policy analysis, or economic briefings where energy sector macro context is needed quickly.
Side effects
- Missing or invalid 'start' date parameter returns an error or unexpected behavior
- Malformed date string may cause upstream data fetch failures
- FRED or World Bank data unavailability may result in incomplete analysis
- LLM inference timeout may cause delayed or failed response
- Costs $0.40 USDC per call via x402 on Base — payment failure blocks access
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| startrequired | string | start |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| data | object | |
| successrequired | boolean |
Tags
x402
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