How to Build a Solana MEV Bot: Stack, Steps and Pitfalls

To build a Solana MEV bot, you need a data feed for on-chain state, a strategy that computes net profit after costs, a simulator, a sender that submits transactions or Jito bundles with a tip, and a wallet with strict risk limits. Build it in that order, and run in simulation for a long time before risking funds.

Decide what you are building first

“MEV bot” covers very different programs. A DEX arbitrage bot, a liquidation bot and a launch sniper have different data needs, risks and competition. Pick one narrow strategy. Beginners who try to build a general-purpose bot end up with a general-purpose mess.

For a first project, arbitrage between two well-known pools is the usual choice, because the logic is simple to state and the downside is limited by atomic execution. Our guide to the Solana arbitrage bot covers the route types and profit arithmetic.

The components

Component	What it does	Beginner option	Later upgrade
Data feed	Provides current pool and account state	Paid RPC provider	Streaming data, dedicated node
Strategy engine	Finds candidates and computes net edge	Simple Rust or TypeScript loop	Parallel, cache-heavy engine
Simulator	Verifies a transaction would succeed	RPC simulate call	Local state simulation
Sender	Builds, signs and submits	Standard RPC	Jito bundles with tip logic
Wallet and risk layer	Holds funds and enforces limits	Dedicated hot wallet, small balance	Multiple wallets, automated stops
Logging and metrics	Records outcomes	Plain log files	Dashboard with profit per attempt

A sensible build order

1. Learn the account model. Solana programs read and write accounts, and a swap is a set of instructions touching specific accounts. Read how transactions are structured, including the versioned transaction format that allows lookup tables for larger routes.
2. Build a read-only monitor. Subscribe to pool accounts and log prices. No keys, no money.
3. Compute net edge. Add pool fees, slippage, base and priority fees, and a notional tip. See the fee documentation for how fees are calculated.
4. Add simulation. Construct the real transactions and simulate them. Log how often a candidate would have succeeded.
5. Add submission through Jito. Wrap transactions in bundles with a tip transfer, following the Jito documentation. Our bundle explainer gives the concept in plain terms.
6. Add risk limits. Maximum position size, maximum loss per hour, maximum failed attempts before a halt, and a manual kill switch.
7. Run a tiny live test. Use a balance you can afford to lose entirely.
8. Measure and iterate. Compare simulated and realised profit.

Key takeaway: the hard part is not sending transactions. It is knowing, before you send, whether the trade will still be profitable after fees, tips and competition.

Languages and tooling

Rust is the usual choice for production because Solana’s tooling is Rust-first and performance matters. TypeScript is fine for prototyping, monitoring and dashboards. Python is useful for analysis of logs and backtests, but not for the latency-critical path. Whatever you choose, keep the strategy logic separate from the transport code so you can swap data sources and senders without rewriting your maths.

Security basics

A bot holds a private key on a machine connected to the internet. That is a risk by itself.

• Use a dedicated wallet funded with only what the bot needs.
• Never reuse your main wallet’s key.
• Keep keys out of source control and out of logs.
• Review every dependency, especially code copied from public repositories. Fake “free bot” repositories that steal keys are a known problem; see our note on open-source bots.
• Set withdrawal and loss limits at the infrastructure level, not just in code.

Build versus buy

Building teaches you what matters and gives you full control, but costs time and has a long path to reliability. Buying saves time but means trusting a vendor’s description of its software. CryptoMEV Bot’s Solana MEV bot page is an example of the bought route: it lists pre-built strategies, wallet-connect setup, a dashboard and a retail price of $1,999 one-time. It does not publish performance figures, so you would be buying on description rather than on a track record. The vendor also publishes a guide to making an MEV bot if you want to compare approaches. For a structured way to judge any product, use our evaluation criteria.

Mistakes that cost beginners money

• Optimising before measuring. Without baseline numbers, you cannot tell whether a change helped.
• Ignoring failed transaction costs. They look small individually and add up.
• Overfitting to one lucky day. A strategy that worked during a volatile hour may not survive a quiet week.
• Running without a kill switch. A bug can drain a balance faster than you can react.
• Skipping the legal and tax questions. Each trade can create a record you need. See legal and tax considerations.

How long until it pays?

Nobody can honestly answer this. Operators who succeed tend to specialise, iterate for months and keep costs low. Many never cover their costs. Plan your first project as education, set a spending cap for infrastructure and time, and stop if the numbers do not improve.

What a first week might look like

Day one is reading: the Solana account model, how swaps are expressed as instructions, and how fees work. Days two and three are a read-only monitor that logs prices from two pools. By day five you can compute net edge on the logged data, and you will probably find it negative most of the time. That is the lesson. Week two adds simulation, week three adds bundle submission on a test balance, and only then does live trading begin, with limits you set in advance.

The temptation is to skip ahead to submission because it feels like progress. Resist it. The monitor and the calculator are where you learn whether a strategy has any chance, and they cost almost nothing.

Data is the quiet bottleneck

Beginners focus on the sending code, but data freshness decides most outcomes. If your picture of pool state is a few hundred milliseconds old, your simulation will pass and your transaction will fail. Paid RPC plans and streaming services exist to shrink that gap, and they are a recurring cost. Measure your own latency: log the time between a pool change on-chain and the moment your bot sees it. If that number is large relative to a slot, no tip policy will rescue the strategy.

Testing and observability

Write tests for the arithmetic first, because a rounding error in profit calculation is the cheapest bug to prevent and the most expensive to ship. Replay recorded state through your strategy engine to see what it would have done. Add structured logs for every candidate: what was found, what was computed, whether it was sent, whether it landed, what it earned. Without that table you are guessing.

Where a vendor might fit

Some builders buy software to skip the plumbing and spend their time on strategy. If you go that way, read what the product actually states. CryptoMEV Bot’s Solana MEV bot page describes a connect, configure, deploy flow and names Raydium, Orca and Solend, but it does not describe the internals, so you would be trusting a black box. Even then, the checklist above applies: small balance, separate wallet, hard limits, and a record of every result. For more background on how that vendor describes MEV in general, its article on how to make an MEV bot is a readable counterpoint to the approach described here.