Telegram Bot for Crypto Trading: How We Make It Faster and Safer
Picture this: a new token on Uniswap V3 adds $200k liquidity. Your bot must buy within 2 seconds, or slippage exceeds 20%. Or you configured a sniper, but it bought a contract with a 99% tax — money lost. Our team builds Telegram bots at the level of Maestro/Banana Gun that solve these problems with transaction simulation in Tenderly, Flashbots Protect, and multi-chain aggregation.
We create full-featured trading protocols with MEV protection, automatic orders, and support for Ethereum, BSC, Arbitrum, Base, and Solana. Each bot is tested on testnets and undergoes smart contract audit. Estimate your project — contact us.
Years of experience in Web3 and dozens of realized trading bots allow us to process transactions worth millions of dollars monthly. In this article, we'll break down the key features that distinguish professional bots from amateur crafts.
How Token Sniping Works
Sniping is the most demanded feature. A new token is deployed on Uniswap, liquidity is added — the bot buys within the first seconds. Let's dive into the key mechanics.
Auto-snipe on new pairs: monitoring Uniswap Factory PairCreated events. When a new pair with matching criteria is detected — automatic purchase.
Launch snipe: the user specifies the token address in advance, the bot prepares the transaction and sends it as soon as liquidity appears.
Anti-honeypot: token verification before purchase:
- Simulate buy + sell: if sell reverts — honeypot
- Check owner functions (mint, blacklist, pause)
- Max wallet/transaction limits
- Tax check: if buy/sell tax > threshold — warning
async def check_token_safety(token_address, amount): # Simulate buy transaction buy_result = await simulate_swap(WETH, token_address, amount) # Simulate immediate sell sell_result = await simulate_swap(token_address, WETH, buy_result.amountOut) # Calculate effective tax effective_tax = 1 - (sell_result.amountOut / amount) return SafetyCheck( can_sell=sell_result.success, tax=effective_tax, warnings=check_contract_functions(token_address) ) What Are Limit Orders and How to Implement Them?
DEXes don't have native limit orders — the bot implements them off-chain. The user sets: "buy TOKEN at $0.05, max 0.5 ETH". The bot monitors the price via WebSocket or polling Uniswap price. Upon reaching the target price — automatic purchase.
Trailing stop: the stop moves up with the price. If TOKEN rises from $0.05 to $0.10, trail stop at 15% = stop at $0.085. When it drops to $0.085 — sell.
DCA (Dollar Cost Averaging)
Automatic purchase on a regular basis: /dca BUY TOKEN 0.1 ETH every 6 hours for 7 days. The bot creates a task in the scheduler, every 6 hours it buys 0.1 ETH regardless of price.
How to Protect the Bot from MEV?
Banana Gun built its competitive advantage on MEV protection. Flashbots Protect: sending transactions via https://rpc.flashbots.net. Transactions are visible only to relayers, not in the public mempool — sandwich attack impossible. Auto slippage selection: analysis of pool depth and calculation of minimum slippage ensuring execution. Gas estimation: smart gas price based on current network conditions. More about Flashbots Protect.
Project Token and Revenue Sharing
Unibot and Banana Gun both launched native tokens. Mechanics:
- Revenue share: a percentage (often 40-50%) of protocol fees is distributed to token holders.
- Fee discount: holders pay a lower trading fee.
- Governance: token = voting rights.
Fee structure: 0.5-1% per swap, additional 0.5% for sniper, 5-10% of copy trading profit. At $50M/day turnover, that's $350K/day revenue.
Multi-Chain Support: Why It Matters
| Network | DEX | Features |
|---|---|---|
| Ethereum | Uniswap V2/V3 | High gas |
| BSC | PancakeSwap | Cheaper |
| Arbitrum | Camelot, Uniswap V3 | L2 |
| Base | BaseSwap, Uniswap V3 | New |
| Solana | Jupiter, Raydium | Different architecture |
Solana requires a separate implementation.
Telegram UI/UX
Inline keyboards for quick actions. When buying — a step-by-step flow: input address, choose amount, confirm with preview, execute, result with link to Etherscan.
Feature Comparison
| Feature | Technical Implementation | Tools |
|---|---|---|
| Sniper | Monitoring Factory events | ethers.js, WebSocket |
| Limit orders | Off-chain price monitoring | PostgreSQL, scheduler |
| MEV protection | Flashbots RPC | @flashbots/ethers-provider |
What's Included in Developing Such a Bot?
- Architecture design and stack selection (Solidity, Foundry, ethers.js/viem)
- Smart contract development (Uniswap integration, custom pool handling)
- Backend on Node.js/Python with queues and WebSocket
- MEV protection setup (Flashbots, private mempool)
- Multi-chain support (EVM + Solana)
- Deployment and monitoring (Docker, Tenderly, Grafana)
- Documentation and team training
Case Study: Reducing Sniper Latency
On a recent project, we optimized a sniper bot for an Ethereum memecoin launch. The initial latency was ~2 seconds from detecting the pair to transaction submission, resulting in high slippage (15-25%). We switched from polling to WebSocket subscriptions on the Uniswap Factory contract, used a dedicated node with low latency, and pre-signed transactions to reduce gas estimation overhead. Final latency dropped to 500ms, and slippage averaged 3-5%. The bot executed 40 buys in the first 30 seconds after liquidity addition.
We have years of experience in Web3 and have delivered dozens of trading bots for various networks. Contact us — we'll evaluate your project and offer custom solutions.