The Future of RPCs: Beyond JSON-RPC to a Universal Query Layer

Raw JSON-RPC forces developers to manage complex logic for data fetching, error handling, and chain-specific quirks. This creates brittle applications and wasted engineering cycles.

• Spaghetti Code: Apps need custom logic for gas estimation, block confirmations, and fallback providers.
• Performance Tax: Sequential calls for simple queries (e.g., token balance + ENS name) create ~300-500ms latency.
• Fragmented DevEx: Each new chain (Ethereum, Solana, Sui) requires learning a new RPC dialect.

Modern RPCs like Chainscore and K2 are adopting a query-based model, inspired by GraphQL and intent architectures like UniswapX. Developers declare what data they need, not how to fetch it.

• Batch Everything: A single query can fetch balances, NFTs, and transaction simulations atomically.
• Chain Abstraction: One standardized interface for Ethereum, Solana, and layerzero-connected chains.
• Cost Efficiency: Aggregated requests reduce provider calls, slashing infrastructure costs by -50%.

Traditional RPC providers are black-box services. They control data access, can censor transactions, and create single points of failure for $10B+ TVL in DeFi.

• Censorship Risk: Providers can front-run or block transactions based on OFAC lists.
• Opacity: No verifiable proof that returned data (e.g., MEV bundle outcomes) is correct.
• Vendor Lock-in: Switching providers requires rewriting application code.

The next evolution is RPCs with cryptographic guarantees, moving towards a model like The Graph but for real-time state. Nodes compete to serve queries, with validity proofs or slashing for incorrect data.

• Provable Data: Light clients can verify query responses via ZK proofs or optimistic verification.
• Anti-Censorship: Query routing through a decentralized network of nodes, similar to POKT.
• Market Efficiency: A competitive marketplace for data service drives down costs and improves uptime.

A vanilla RPC has no awareness of the application using it. It can't prioritize queries for a high-frequency DEX vs. a wallet, optimize for latency vs. cost, or pre-fetch predictable data.

• Blind Optimization: The infra doesn't know if a query is for a UI render or a back-end settlement.
• No Personalization: Can't tailor data streams (e.g., NFT metadata + floor price) for specific app needs.
• Inefficient Caching: Generic caching strategies miss app-specific data patterns.

RPC endpoints become programmable execution environments. Inspired by account abstraction and session keys, apps can define policies for gas sponsorship, query batching, and real-time data streams.

• App-Specific Logic: Define rules like "sponsor gas for first-time users" or "stream all new Uniswap pools".
• Predictive Pre-fetching: The RPC learns app patterns to cache data before it's requested.
• Monetization Layer: Developers can offer premium, context-aware data services directly through the RPC.

Universal layers risk becoming centralized choke points, replicating the very problem they aim to solve. A single provider controlling the gateway to all chains creates a systemic SPOF.

• Censorship Risk: A single entity can filter or block transactions.
• Data Integrity: A compromised aggregator could serve maliciously altered state data.
• Vendor Lock-in: Protocols become dependent on a single query API, stifling competition.

Aggregating data from multiple sources for intent execution creates a new oracle problem. The layer must decide which chain state is 'true' for cross-chain queries, opening vectors for manipulation.

• Timing Attacks: Adversaries can exploit latency differences between chains.
• Settlement Ambiguity: Conflicting finality guarantees (e.g., Solana vs. Ethereum) make consistent views impossible.
• Frontrunning: The query layer itself could become a privileged MEV searcher.

To be universal, the query layer must embed validation logic for every supported chain, creating a massive, fragile client. Light clients for dozens of chains are impractical, forcing users to trust the layer's attestations.

• Security Dilution: A bug in one chain's adapter compromises the entire system.
• Trust Assumption: Users must verify a signature from the layer, not the underlying chain.
• Update Lag: Slow to integrate new chains or consensus changes, reducing universality.

Dominant Layer 1s like Ethereum and Solana have no incentive to cede control of their primary interface. They could degrade performance for universal RPCs or make proprietary extensions standard, fragmenting the landscape.

• API Sabotage: L1s could rate-limit or deprioritize aggregated queries.
• Ecosystem Lock-in: Promotion of native tooling (e.g., Ethers.js, Solana Web3.js) over universal standards.
• Revenue Cannibalization: L1s profit from their own RPC services; a universal layer threatens this.

Today's RPC endpoints are centralized chokepoints for latency, censorship, and downtime. A single provider outage can brick dApps for millions of users.

• Downtime Risk: A single provider failure can cause ~100% API error rates for dependent dApps.
• Censorship Vulnerability: Providers can be forced to filter transactions, breaking neutrality.
• Performance Lottery: Latency varies wildly (200ms to 2s+) based on geographic load and provider health.

Replace single endpoints with a peer-to-peer network of independent node providers. This creates redundancy, competitive pricing, and censorship resistance.

• Redundant Uptime: Requests are routed across hundreds of nodes, eliminating single-provider risk.
• Market-Driven Pricing: Providers compete on price and quality, reducing costs by ~30-50%.
• Universal Access: A single integration supports EVM, Cosmos, Solana, and more, via a unified API.

The endgame is moving beyond low-level eth_call to a universal query layer. Developers declare what data they need, not how to fetch it, similar to the shift from Uniswap v2 to UniswapX.

• Abstraction: Request "best price for 100 ETH to USDC" instead of manually calling multiple DEX contracts.
• Optimized Execution: The network finds the optimal data source or route, slashing latency by 10x.
• Composability: Enables new primitives like account abstraction and cross-chain intents pioneered by Across and LayerZero.

Token-incentivized networks like Pocket use a staking mechanism to align provider incentives with reliable service, moving beyond pure SaaS pricing.

• Skin in the Game: Providers stake native tokens; poor performance or downtime leads to slashing.
• Sybil Resistance: Staking requirements prevent spam and ensure node operator commitment.
• Earn-While-You-Serve: Node operators earn fees in the network token, creating a permissionless marketplace for RPC services.