How to Architect a Searcher-Builder Marketplace

A searcher-builder marketplace is a specialized platform that facilitates the exchange of transaction bundles between two key actors in the Ethereum ecosystem: searchers and builders. Searchers are sophisticated users who identify profitable opportunities (like arbitrage or liquidations) and craft complex transaction bundles to capture that value. Builders are specialized block producers who compete to construct the most valuable block for proposers by including these bundles. The marketplace's architecture defines the rules, communication protocols, and economic incentives that govern this interaction, aiming to maximize efficiency and value for all participants.

The core architectural components are the auction mechanism, the communication relay, and the trust model. The auction is the heart of the marketplace, where builders bid for the right to include a searcher's bundle. Common designs include first-price sealed-bid auctions or mev-geth's open bidding. The relay is the infrastructure that transmits bundles from searchers to builders and validated blocks from builders to proposers, ensuring data integrity and censorship resistance. The trust model, often enforced via commit-reveal schemes and slashing conditions, prevents malicious behavior like frontrunning or non-inclusion after payment.

Implementing the marketplace requires a clear API for searchers. A typical submission endpoint accepts a signed bundle with parameters like max_block_number, min_timestamp, and a refund_recipient. The backend must validate bundle semantics, simulate execution to ensure profitability and safety, and then broadcast it to connected builders. Builders, in turn, integrate a client that listens for these bundles, evaluates them against their own block construction strategy, and submits bids back to the marketplace. The winning builder's block is then delivered to a trusted relay for proposers.

Security is paramount. Architectures must guard against timing attacks where a malicious actor intercepts a bundle. Using encrypted mempools or direct peer-to-peer channels between searchers and trusted builders can mitigate this. Economic security is enforced through builder deposits that can be slashed for equivocation or withholding winning bids. Furthermore, the marketplace should implement reputation systems to penalize builders who consistently fail to include winning bundles or searchers who submit invalid transactions, creating a healthier ecosystem.

For a practical example, consider a simple auction contract. A searcher calls submitBundle(bytes bundleHash, uint256 bid) which locks their bid. Builders submit their commitment commit(bytes32 sealedBid). In a reveal phase, builders reveal their actual bid. The contract then selects the highest valid bid, pays the searcher, and slashes any builder that revealed incorrectly. This on-chain component, combined with off-chain relay infrastructure for speed, forms a hybrid architecture balancing security with the low-latency demands of block production.

The future of these marketplaces involves increased specialization and integration with SUAVE (Single Unifying Auction for Value Expression). SUAVE aims to become a decentralized block builder and preference network, potentially standardizing marketplace interfaces. Architects today should design for modularity, allowing components like the auction engine or relay network to be upgraded or replaced. Focusing on minimal trust assumptions, maximal extractable value (MEV) redistribution to users, and robust censorship resistance will define the next generation of searcher-builder platforms.

A searcher-bundler marketplace is a specialized platform that connects MEV searchers with block builders via a bundler service. The core function is to aggregate, order, and submit user transactions from a decentralized application's mempool, making them attractive for inclusion in a block. This architecture is fundamental for applications like account abstraction (ERC-4337) wallets and intent-based systems, where user experience depends on reliable and efficient transaction processing. Understanding this three-party model—user, bundler, builder—is the first prerequisite.

The technical stack requires deep integration with Ethereum's execution and consensus layers. You will need to run or connect to an execution client (e.g., Geth, Erigon) to access the transaction mempool and simulate bundles. A builder API endpoint (e.g., the Ethereum Builder API specification) is necessary to communicate with professional block builders like Flashbots, Titan, and rsync. The bundler itself must implement ERC-4337's Bundler specification, handling UserOperation objects, performing paymaster sponsorship checks, and ensuring atomic bundle execution.

Economic design is critical for sustainability. The marketplace generates revenue primarily through priority fees (tips) included in bundled transactions. A portion of this fee is typically shared with the searcher who identified the opportunity. You must design a fee distribution model and a bidding mechanism where searchers compete for bundle inclusion. Furthermore, the bundler must manage stake (either directly or via a solver in an intent system) to participate in builder auctions and provide credible commitment, penalizing invalid bundles.

Key operational challenges include simulation and risk management. Every potential bundle must be simulated against the latest chain state to ensure it is valid and profitable, using tools like Geth's eth_call or specialized MEV frameworks. The bundler must guard against reversion attacks, where a searcher's bundle fails on-chain, wasting the builder's block space and jeopardizing the bundler's reputation and stake. Implementing reputation systems for searchers and fallback RPC providers is essential for maintaining reliability.

To begin development, familiarize yourself with the core specifications: the ERC-4337 account abstraction standard and the Flashbots MEV-Boost relay/builder architecture. Open-source references like the Ethereum Foundation's 4337 bundler implementation or Stackup's bundler provide a practical starting point. The next steps involve setting up a testnet environment, integrating with a builder API, and designing your marketplace's logic for searcher onboarding, bundle valuation, and fee extraction.

A searcher-bundler marketplace operates as a first-price sealed-bid auction. Searchers, who construct complex transaction bundles (e.g., for MEV extraction or user operations), submit their bundles to the marketplace along with a bid representing the maximum fee they are willing to pay for inclusion. Crucially, they do not see the bids of their competitors. The bundler (or auctioneer) collects these sealed bids, selects the most profitable set of non-conflicting bundles, and submits them to the blockchain. The winning searchers pay the exact amount they bid. This design prioritizes revenue maximization for the bundler and creates a straightforward, incentive-compatible environment for participants.

The auction's design must enforce atomicity and conflict resolution. Two bundles that access the same on-chain state (e.g., arbitraging the same DEX pool) cannot be included in the same block as they would revert. The bundler's solver must therefore solve a combinatorial optimization problem: select the subset of submitted bundles that maximizes total bid value while guaranteeing no state conflicts. This is often implemented using a greedy algorithm or more advanced solvers for larger markets. The Ethereum Builder-Bid Spec provides a foundational framework for such auction mechanics, adapted here for the pre-chain searcher layer.

Key parameters must be defined in the smart contract governing the auction. These include the minimum bid increment, auction round duration (e.g., every block or a fixed time window), and payment settlement logic. A common pattern is for the bundler to act as the block builder or to sell the winning bundle to a builder via a relay. The contract must also handle edge cases like reverting bundles, ensuring the bundler is compensated for base gas costs even if a searcher's bid fails to cover them. This requires a robust bid validation stage that simulates bundle execution off-chain before final selection.

For developers, the core auction logic can be prototyped in a smart contract. A simplified version involves a submitBundle function that accepts bytes calldata bundleData and uint256 bidAmount, storing them in a mapping keyed by bundle hash. An auctioneer role then calls a settleAuction function which, in a simplified form, might select the single highest bid, check for conflicts via a simulated call, and then execute the winning bundle. In practice, systems like the SUAVE initiative by Flashbots are building generalized decentralized blockspace auctions that abstract this complexity.

The core of the marketplace's security model is a reputation system that tracks each searcher's performance. This isn't just a simple score; it's a multi-dimensional metric that should account for bundle success rate, MEV extraction efficiency, gas optimization, and crucially, historical compliance with the protocol's rules. A high reputation score grants a searcher priority in the bundler's ordering algorithm and can lead to reduced fees or collateral requirements. This system incentivizes long-term, honest participation over short-term exploitation.

Slashing is the enforcement mechanism that backs the reputation system. It involves the partial or total confiscation of a searcher's staked collateral as a penalty for provably malicious actions. Key slashable offenses include: bundling front-running transactions against the user's intent, including censored transactions, failing to execute a winning bundle (non-performance), and submitting bundles with invalid state transitions. The slashing conditions must be objectively verifiable on-chain to avoid subjective disputes, often relying on fraud proofs or zk-SNARKs.

Here is a simplified conceptual structure for a searcher's on-chain state, often implemented as a smart contract storage variable:

solidityCopy
struct SearcherReputation {
    uint256 stake; // Locked collateral
    uint256 reputationScore; // Composite score (0-1000)
    uint32 successfulBundles;
    uint32 failedBundles;
    uint256 lastSlashTime;
    bool isSlashed;
}

The reputationScore would be updated by the bundler or a dedicated reputation oracle after each bundle settlement, factoring in the new outcome.

Implementing slashing requires a dispute resolution period. When a slashable offense is detected, typically by a network of watchers, a slashing proposal is submitted. The searcher then has a window (e.g., 24-48 hours) to provide a counter-proof. If no valid counter-proof is provided, the slashing is executed automatically, distributing a portion of the seized stake to the reporter and the protocol treasury. This design aligns with the "verify, then trust" principle common in decentralized systems.

For a production system, consider integrating with a secure off-chain computation network like Chainlink Functions or API3 to fetch complex reputation metrics. Furthermore, the initial slashing parameters—like stake amounts and penalty percentages—should be governed by a DAO to allow for community-driven adjustments as the market evolves. The goal is to create a self-regulating ecosystem where quality is rewarded and bad actors are economically disincentivized.

The core economic mechanism of a searcher-bundler marketplace is its fee structure. This model must balance three objectives: compensating the bundler for its operational costs (e.g., gas, RPC calls), incentivizing searchers to submit high-quality bundles, and remaining competitive for end-users. A poorly designed fee model can lead to misaligned incentives, where bundlers operate at a loss or searchers are disincentivized from participating. The primary components are the bundler fee (paid by the searcher) and the user fee (paid by the end-user, often embedded in the transaction).

Common fee models include fixed fees, percentage-based fees, and auction-based fees. A fixed fee per bundle is simple but doesn't scale with bundle value. A percentage fee (e.g., 0.5% of the bundle's total MEV value) aligns bundler revenue with the value it facilitates but can be complex to calculate. The most sophisticated approach is a first-price sealed-bid auction, where searchers bid for inclusion in the next block. The bundler selects the highest bid, maximizing its revenue while allowing searchers to express their private value for transaction ordering.

Implementation requires smart contract logic to collect, distribute, and potentially slash fees. The bundler's smart contract must securely accept payment, often in ETH or a stablecoin like USDC, and route it to the bundler's treasury. Consider implementing a fee escrow or bonding mechanism where searchers deposit funds that can be slashed for submitting invalid bundles, protecting the bundler from spam and failed transactions. The contract should emit clear events for all fee transactions to ensure transparency and auditability.

For example, a simplified fee function in a bundler contract might look like this:

solidityCopy
function submitBundle(Bundle calldata _bundle, uint256 _bid) external payable {
    require(msg.value >= _bid, "Bid must be covered");
    require(_bid >= minBid, "Bid below minimum");
    // ... bundle validation logic ...
    pendingBundles[msg.sender] = _bid;
    emit BundleSubmitted(msg.sender, _bid, block.timestamp);
}

After the bundle is executed on-chain, a separate function would finalize the payment, transferring the bid from escrow to the bundler's address.

Finally, the fee structure must be adaptable. Monitor key metrics like searcher participation rate, average bid value, and bundle failure rate. Be prepared to adjust parameters like minimum bids or fee percentages based on network conditions (e.g., base layer gas prices) and competitive dynamics. The goal is a self-sustaining ecosystem where all participants are fairly compensated for the value they provide.

Liveness ensures the marketplace can always accept and process user intents, while censorship resistance guarantees no valid transaction can be blocked. A centralized bundler or a single point of failure in the relay network directly threatens both. The primary architectural defense is decentralization at the relay layer. Instead of a single endpoint, users and searchers should be able to submit bundles to a permissionless network of relay nodes, similar to the peer-to-peer mempool in Ethereum. Projects like EigenLayer and AltLayer provide frameworks for building decentralized networks of verifiable nodes that can serve this purpose.

To coordinate this decentralized network, a consensus mechanism is required for bundle ordering and inclusion. A simple first-price auction conducted on-chain can be vulnerable to MEV and last-block reorgs. More robust solutions implement a commit-reveal scheme or use a verifiable random function (VRF) for fair leader election among relays. The SUAVE (Single Unifying Auction for Value Expression) design, proposed by Flashbots, envisions a decentralized block-building network where searchers submit encrypted bids to a network of executors, which then compete to create the most valuable block in a trust-minimized way.

Smart contracts play a critical role in enforcing these rules and slashing malicious actors. The core marketplace contract should manage the bonding and slashing of relay operators. Operators must stake a security deposit (bond) that can be slashed for liveness failures—like going offline—or for censorship—like excluding a valid, fee-paying bundle. The contract logic must define clear, verifiable conditions for slashing, often relying on fraud proofs or cryptographic attestations from other network participants.

From a searcher's perspective, client software must be designed to broadcast bundles to multiple relays concurrently. This requires implementing a redundancy layer that submits the same bundle to several relay endpoints and monitors for inclusion. A simple implementation in TypeScript for an ethers.js-based searcher might involve wrapping the bundle submission in a Promise.race() against a list of relay RPC URLs. This ensures the bundle reaches the chain as long as at least one honest relay is operational.

Finally, economic incentives must align to sustain the network. Relay operators earn fees from included bundles, but the protocol must ensure these fees are sufficient to cover operational costs and the opportunity cost of staked capital. Fee distribution mechanisms should reward relays for honest participation and timely inclusion. Furthermore, a portion of transaction fees can be directed to a liveness fallback fund, which automatically pays for transaction inclusion via a secondary channel (like a public mempool) if the primary relay network fails, creating a robust safety net for end-users.

Building a functional marketplace requires integrating the components we've discussed: a bundler to construct and submit transactions, a searcher API for order flow, a mempool watcher for opportunity discovery, and a reputation/auction system for fair allocation. The key is to start with a minimal viable product (MVP) that connects a single searcher to your bundler using a simple first-price auction. This allows you to validate the core transaction pipeline on a testnet like Sepolia or Holesky before introducing complexity.

For production, focus on robustness and security. Your bundler must handle transaction simulation and validation to prevent failed bundles, which waste gas and harm searcher trust. Implement a fallback RPC provider strategy to maintain uptime. Security audits for your smart contracts (like a staking contract for searchers) and API endpoints are non-negotiable. Consider using established libraries like userop.js for bundler logic to reduce implementation risk.

To scale and improve the system, iterate on the auction mechanism. A simple first-price auction can be replaced with a second-price (Vickrey) auction or a PGA (Priority Gas Auction)-style model to reduce searcher overbidding. Introduce a reputation score for searchers based on metrics like bundle success rate, profit consistency, and latency. This score can influence bundle allocation or stake requirements, creating a competitive, high-quality marketplace.

Finally, analyze and optimize for performance. Monitor key metrics: bid-to-win ratio, average profit per bundle, end-to-end latency (from opportunity detection to on-chain inclusion), and bundle failure rate. Use this data to refine your mempool filtering algorithms and bidding strategies. The goal is to create a feedback loop where better data attracts better searchers, which in turn improves overall marketplace efficiency and profitability for all participants.