Integrating a Bot with STON.fi DEX on the TON Blockchain

We integrate trading bots with the STON.fi SDK for automated trading on the DEX in the TON blockchain. TON is fundamentally different from EVM: it has an asynchronous message model, an actor model, and unique fee mechanics. Our experience in blockchain development (5+ years, over 10 projects on TON) allows us to account for all the nuances and build a reliable turnkey bot.

Why TON Is Harder Than EVM for a Bot

Asynchronous Transaction Model

In Ethereum, a transaction either executes or reverts — everything is synchronous within one block. In TON, contracts communicate via asynchronous messages. After sending a swap message to the STON.fi router, you don't know the result immediately. You need to listen for incoming messages on the wallet address (transfer notification from jetton) or poll state via the TON API.

This means the bot must have a state machine for each operation. Send a swap → wait for confirmation → if none within N seconds → retry or alert. A simple send-and-forget logic leads to lost transactions.

Each message in TON is encoded as a Bag of Cells (BoC). Parsing incoming notifications requires decoding the BoC and extracting fields such as jetton amount and sender. The STON.fi SDK provides types for this, but integration requires setting up a TON listener.

The official STON.fi SDK documentation recommends using queryId to track operations — it is included in response messages and allows you to match a request with a result.

How to Integrate a Bot with the STON.fi SDK

Installation and Configuration

import { DEX, pTON } from "@ston-fi/sdk";
import TonWeb from "tonweb";

const tonweb = new TonWeb(
  new TonWeb.HttpProvider("https://toncenter.com/api/v2/jsonRPC", {
    apiKey: process.env.TONCENTER_API_KEY
  })
);

const router = tonweb.open(
  new DEX.v1.Router("EQB3ncyBUTjZUA5EnFKR5_EnOMI9V1tTEAAPaiU71gc4TiUt")
);

The STON.fi SDK v2 supports DEX v1 and v2 pools. For new code we use the v2 router — it supports more complex routing scenarios and better API integration.

Getting Quotes

const pool = await router.getPool({
  token0: "EQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAM9c",  // TON
  token1: USDT_JETTON_ADDRESS
});

const data = await pool.getData();
// data.reserve0, data.reserve1 — current reserves
// Calculate expected output via AMM formula

The SDK provides getExpectedOutputs() for slippage calculation. Important: quotes become stale quickly in an active market. For a trading bot, cache for no longer than 5–10 seconds.

Executing a Swap

const swapTxParams = await router.buildSwapTonToJettonTxParams({
  userWalletAddress: wallet.address,
  proxyTon: new pTON.v1(),
  offerAmount: new TonWeb.utils.BN("1000000000"),  // 1 TON in nanotons
  askJettonAddress: USDT_JETTON_ADDRESS,
  minAskAmount: expectedOutput.mul(99).div(100),  // 1% slippage tolerance
  queryId: Date.now()  // unique ID for tracking
});

await wallet.sendTransfer({
  secretKey: keyPair.secretKey,
  toAddress: swapTxParams.to,
  amount: swapTxParams.gasAmount,
  seqno: await wallet.getSeqno(),
  payload: swapTxParams.payload
});

queryId is a critical parameter for tracking. It is included in response messages and allows you to match the swap request with the result in the asynchronous model.

How to Build a Trading Bot Architecture for TON

Price monitor: periodic polling of prices via the STON.fi API (https://api.ston.fi/v1/pools) or direct on-chain requests. The API is more convenient — it returns normalized data for all pools. On-chain is more reliable when the API is unreliable.

Strategy engine: logic for trading decisions. For an arbitrage bot — compare STON.fi prices with other TON DEXs (DeDust). For a trend-following bot — technical indicators on historical prices from the API.

Transaction manager: a queue of transactions with retry logic. TON requires a correct seqno for the wallet — parallel sending leads to errors. We send transactions sequentially or via separate sub-wallets.

Result tracker: polling the wallet's latest transactions via the TON API to confirm swap execution. https://toncenter.com/api/v2/getTransactions?address=...

Gas Management on TON

TON uses a gas model different from Ethereum. For a jetton swap, you need to send enough TON to pay forward fees along the message chain: router → jetton wallet → user wallet. The STON.fi SDK returns the correct gasAmount in buildSwapTxParams — do not reduce it "to save". If gas is insufficient, the message simply won't reach its destination, and funds may get stuck at an intermediate contract. Optimizing gas can save up to 30% on commissions, and fixed development cost prevents budget overruns.

What Our Work Includes

All work is carried out turnkey with a 30-day warranty on any bugs found. We use formal verification for critical contracts.

Our Experience and Guarantees

• Web3 development experience since 2019, over 10 projects on TON/STON.fi
• Security guarantee: code is checked with Slither, Mythril, and Echidna
• Certified engineers (Ethereum, Solana, TON)
• Up to 30% savings on commissions through gas optimization

Contact us for an assessment of your project. We'll propose an optimal turnkey solution in 1–2 weeks. Get a consultation on integration today.

Links:

• STON.fi SDK on GitHub
• TON Blockchain on Wikipedia

DeFi Protocol Development

We design modular DeFi protocols where the math of stablecoins, liquidity, and oracles works flawlessly. Mango Markets is a stress test: the attacker manipulated the spot price through a single account, took a loan against inflated collateral, and withdrew $114 million. The oracle took the price from a single source without TWAP. Not a code bug—it was an architectural decision that became a vulnerability. Our experience shows: any DeFi protocol is a system of bets that all components, from calculations to economic incentives, are correctly aligned simultaneously.

We don't write code under the 'if it works, don't touch it' mindset. We model stress scenarios: cascading liquidations, depegs, flash loans. Only then do we build events that won't break the protocol.

Why are oracles a critical component of DeFi?

Most major DeFi hacks started with oracle manipulation. Let's break down the three layers we use in every project.

Spot price as oracle—not an option. Uniswap v2 spot price can be shifted by a flash loan in one transaction. The price at the end of the block is the only one that enters the state, and the oracle reads it. Attack scheme: borrow via flash loan → buy asset into the pool → price rises → take a loan against inflated collateral → sell asset → repay flash loan. One transaction.

TWAP as protection. Uniswap v3 observe() averages the price over a period (30 minutes). Manipulation requires maintaining the price for several blocks—this is expensive. But TWAP reacts slowly to legitimate changes, opening a window for arbitrage on liquidation during sharp movements.

Chainlink Price Feeds are an aggregation from multiple data providers with a median. Standard for lending. Problem: heartbeat 1–24 hours and deviation threshold 0.5%. If the price doesn't move, the feed may not update for a day. In volatile markets—lag.

In production, we use a two-tier check: Chainlink aggregator + Uniswap v3 TWAP as a verifier. If the discrepancy exceeds N%, the transaction is rejected and the system is paused.

How to protect a DeFi protocol from flash loan attacks?

Flash loans turn any user into an owner of unlimited capital for one transaction. Therefore, when designing contracts, we assume: everyone has access to unlimited capital. This completely changes the threat model.

Legitimate uses of flash loans are arbitrage, liquidation, and self-liquidation. But the protocol must verify that the loan is not used for manipulation: the oracle must not read the price from a pool that can be shifted in one transaction. We add checks on block.timestamp and minimum liquidity depth.

Key Components of DeFi Architecture

AMM: From x*y=k to Concentrated Liquidity

Uniswap v2 uses x * y = k. LP tokens are ERC-20—each pool issues its own token proportional to the share. Problem: liquidity is spread across the entire curve, most of it unused.

Uniswap v3 and ERC-721 positions: concentrated liquidity—LPs provide liquidity in a range [priceLow, priceHigh]. Capital efficiency up to 4000x for stable pairs. But ERC-721 breaks vault strategies built for ERC-20. Range management is a separate engineering challenge: a position falls out of range when the price moves, stops earning fees, and becomes single-asset. Protocols like Arrakis Finance automatically rebalance. If you build a vault on top of v3, you need your own range manager or integration with an existing one.

Slippage in v3 is calculated via sqrtPriceX96—96-bit fixed-point math. Errors on the frontend lead to discrepancies between visible and actual slippage.

Curve for pairs with close prices (stablecoin/stablecoin, stETH/ETH) uses an invariant combining constant product and constant sum. Lower slippage within the peg range. Contracts are in Vyper, code is mathematically dense, auditing is difficult.

Lending Protocols: Collateral, Liquidation, Bad Debt

LTV defines the maximum loan against collateral. Liquidation threshold is the level for liquidation. The difference is the buffer for the liquidator. Typical example: LTV 75%, liquidation threshold 80%, bonus 5%. If the price drops 20%+, the position is open for liquidation.

Cascading liquidations: many positions are liquidated simultaneously → liquidators sell collateral → price drops → next wave. LUNA/UST 2022 is a classic cascade.

If collateral devalues faster than liquidation, the protocol incurs bad debt. Aave uses a Safety Module (staked AAVE), Compound uses reserves. Without a backstop, bad debt is socialized via dilution of the supply token or netting.

Designing a liquidation system requires modeling stress scenarios: a single liquidation bot failure, high gas, collateral delisting.

Yield Farming and Incentive Mechanics

Liquidity mining distributes governance tokens to LP providers. Problem: mercenary capital—farmers come, sell tokens, leave. TVL is illusory.

Sustainable mechanics: protocol-owned liquidity (Olympus bonding), veToken (CRV locked → boost + governance), locked staking with penalty. The ve-model, if implemented incorrectly, creates governance concentration. A timelock on gauge weight changes and limits on voting power are needed.

What Our DeFi Protocol Development Includes

• Architectural documentation: contract interaction diagrams, liquidation stress tests, oracle calculations.
• Implementation in Solidity 0.8.x with OpenZeppelin 5.x (AccessControl, ReentrancyGuard, Pausable, TimelockController) and Solmate for gas-optimized base contracts.
• Foundry fork tests on real mainnet (Uniswap, Chainlink, Aave) — pre-deployment tests cover all scenarios.
• Audit: at least two independent auditors for TVL over $1M. Code4rena or Sherlock for bug bounty.
• Deployment with Gnosis Safe 3/5 multisig + timelock 48–72 hours.
• Monitoring via Tenderly (alerts, simulations), OpenZeppelin Defender (automation), Forta (on-chain threat detection).
• Post-launch support: updates, patches, upgrades via proxy.

Our Expertise and Experience

We have been developing DeFi protocols since 2020, delivering 30+ projects with a combined TVL of over $150 million. Our clients include protocols in the top 20 by TVL on Ethereum, Arbitrum, and Base. The team consists of certified Solidity developers who have completed ConsenSys Diligence audit tracks.

DeFi basic principles that we apply in practice.

Timelines

• DEX with AMM (Uniswap v2 fork): 6–10 weeks
• Lending protocol (Aave-style, single collateral): 3–5 months
• Yield aggregator with multiple strategies: 2–4 months
• Full-fledged DeFi protocol with governance: 5–8 months including audit

Cost is calculated individually—contact us for a project estimate.

Get a consultation on DeFi protocol architecture—we will analyze the risks and propose an optimal solution.