FinzData
by FastDrop
Point-in-time market data and server-side backtests: stocks, ETFs, futures, GEX, macro, crypto.
Point-in-time market data and server-side backtests: stocks, ETFs, futures, GEX, macro, crypto. Official MCP Registry: com.finzdata/mcp@1.0.0. Remote endpoint: https://api.finzdata.com/mcp
Problem it solves
Discoverable MCP server listed in the official MCP Registry.
How it's different
Remote MCP endpoint ingested from the official registry and probed by FastDrop.
Ingested from the official MCP Registry
FastDrop pulled this entry from the official MCP Registry as com.finzdata/mcp and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed
and the description is not theirs.
If this is your server, claim the listing to edit it and take ownership. The registry index lists everything else still awaiting a probe.
Claim this listingTools this endpoint exposes
Read directly from the endpoint on 8 Nov 2026. Not supplied by the maker.
search_datasetsFull-text search over the dataset catalog. Returns matching dataset ids and descriptions. Free of look-ahead concerns; no as_of needed.
describe_datasetReturns the schema, coverage and field definitions of one dataset. Raises not_found for an unknown dataset id.
get_universeReturns every US symbol that was trading on as_of, including companies that later delisted (survivorship-free). index='top500'|'top1000'|'top3000' instead returns the most-traded names priced at least
get_barsReturns daily OHLCV bars for symbols between start and end, clipped to as_of (default today) so no future data leaks. Max 5000 rows per page; use next_cursor for more.
backtest_exportDaily OHLCV bars for one symbol packaged as ready-to-load files for an open-source backtester or trading framework: backtrader, backtesting_py, vectorbt, zipline (csvdir bundle), lean (QuantConnect LE
get_fundamentals_pitReturns fundamentals for one symbol as known on as_of (no restatements from the future). as_of defaults to today.
get_macro_vintageReturns a macro series as it was actually published by as_of (vintage data, no revisions from the future). Optional start.
get_quant_modelThe FinzData Quantitative Model as known on as_of: macro regime labels (financial conditions direction, financial risk direction, growth level and direction, inflation direction, macro quadrant GOLDIL
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