🔮Madjik

SDKs

The same data as the API and MCP, in the tools you already use. Retries, rate limits, history paging and webhook checks are handled, so you write the analysis, not the plumbing.

REST APIAny language, webhooks, exports MCPAI assistants and agents
SDKsPython, TypeScript, Google Sheets

Python

  • Pandas-ready, typed errors, retries that honour Retry-After
  • panel(): several metrics on one UTC index, paged through your plan's limits, cached on disk, resumable
  • Point-in-time history (live_only) and look-ahead-safe joins
  • Webhook receiver for FastAPI and Flask

TypeScript / JavaScript

  • Zero dependencies, Node 18+, fully typed
  • The same retries, history and exports
  • Webhook verification and an Express handler

Google Sheets

  • =MADJIK("M10004") in any cell
  • All metrics in one cached call, so a large sheet costs one API call per refresh
  • History, freshness and status functions

Install

pip install https://docs.madjik.io/sdk/madjik-0.2.0-py3-none-any.whl          # Python 3.9+
npm install https://docs.madjik.io/sdk/madjik-0.2.0.tgz                       # Node 18+

Served from docs.madjik.io under the MIT licence, with checksums on the SDK page; PyPI and npm listings to follow. The Sheets script is on the same page.

A backtest dataset in a few lines

from madjik import Madjik
mj = Madjik()                                             # reads MADJIK_API_KEY
mj.plan_calls(["M10004", "M10005"], start="2026-09-01")   # dry run: calls needed vs your daily quota
df = mj.panel(["M10004", "M10005"], start="2026-09-01", live_only=True, lag=1)
print(df.tail())

🚀 Get API Access Now   Read the SDK docs

Madjik metrics are informational market indicators, not investment advice.