SDK MCP server

MarginPad SDK

Free crypto-futures paper trading for bots and free market data. One key, no KYC, no deposit. Test a strategy or an AI agent against live prices with real fee schedules, funding, liquidations, limit and stop orders, trailing stops, webhooks and a WebSocket stream, then take the same code to a real exchange.

• Guide: https://marginpad.io/trading-api/
• Reference (OpenAPI, try it live): https://marginpad.io/api-docs/
• Status: https://marginpad.io/status/ - Changelog: https://marginpad.io/api/changelog.xml
• MCP server for Claude, ChatGPT and Cursor: https://marginpad.io/trading-api/#mcp

Install

pip install marginpad            # Python 3.8+, no dependencies (pip install "marginpad[stream]" for the WebSocket)
npm install marginpad            # Node 18+, zero dependencies

Python

from marginpad import MarginPad

mp = MarginPad("mpb_...")                                   # key from https://marginpad.io/trading-api/
print(mp.price("BTC"))                                      # keyless market data
pos = mp.open("BTC", "long", margin_usd=100, leverage=10, sl=58000, tp=66000,
              client_order_id="sig-2026-09-12-1403")        # idempotent: a retry returns the same position
mp.sltp(pos["id"], trail_pct=1.5)                           # trailing stop, ratcheted server-side
print(mp.account())

JavaScript

const { MarginPad } = require('marginpad');
const mp = new MarginPad('mpb_...');
const { position } = await mp.open({ symbol: 'BTC', side: 'long', margin_usd: 100, leverage: 10, client_order_id: 'sig-1' });
mp.stream(ev => console.log(ev.type, ev.data));             // positions pushed on change, prices each tick

Books, reset, equity, replay (2.5 / 2.6)

mp.accounts()                                   # every book of the account with lifetime numbers
mp.reset()                                      # this key's book back to $10,000 (archived, never deleted)
mp.equity(days=30, step_min=60)                 # equity curve + max drawdown
mp.replay_start("BTC", "2026-09-11", speed=120) # run the same code through a past day, 12 minutes per day
mp.replay(interval=5, bars=120)                 # cursor, price, candles up to the cursor
mp.replay_stop()                                # summary: closes, win rate, P&L, return, liquidations

A key minted with book ({"act":"create","name":"rsi","book":"rsi"} on POST /api/bot/key) trades a separate journal: one strategy, one key, one clean result. During a replay every trading call of that key acts on a replay journal priced from the candle under the cursor; stops, targets and liquidations are checked on every candle between two calls.

Examples

• examples/agent_loop.py: a signal loop that opens, manages and closes positions once a minute without polling storms.
• examples/webhook_server.js: receive position.closed / order.filled events with signature verification.
• examples/mcp.md: let Claude Desktop or Cursor trade on your paper account through the MCP server.

Limits

Free: 120 requests/minute per key, 3 keys, 50 open positions. Premium: 600/minute, 10 keys, 200 open positions. Every response carries X-RateLimit-Limit / Remaining / Reset; on 429 both clients wait Retry-After and retry once. Out-of-range input is refused with a named error (leverage_max carries the market's cap), never silently clamped.

Honesty note

This is a simulator. Fees, funding and liquidation math mirror real exchanges; there is no order book, so slippage is modelled, not measured on depth. A bot that passes here still needs a small live test. Educational use, not financial advice.

MIT licensed.