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go-hyperliquid vs Katoshi

Hyperliquid ecosystem comparison · SDKs & Developer Tools

Ecosystem Pick
Different Focus Areas

Quick Take

go-hyperliquid Community Golang SDK for the Hyperliquid API with concurrent streaming support on Multi-Layer, while Katoshi AI-powered trading automation engine built exclusively for Hyperliquid on HyperCore. They serve different niches in the Hyperliquid ecosystem.

Based on public data for go-hyperliquid and Katoshi. Key differentiators: layer deployment, fee structure, liquidity depth, and community adoption. Last reviewed: Mar 2026.

Overview

go-hyperliquid

go-hyperliquid is a community-developed Golang SDK for the Hyperliquid API, providing idiomatic Go bindings for trading, market data, and account management on Hyperliquid. Built with Go's concurrency model in mind, the SDK leverages goroutines and channels for efficient WebSocket streaming and concurrent order management—making it well-suited for high-throughput trading systems written in Go. The library covers the full Hyperliquid API including REST endpoints for order placement, account queries, and historical data, as well as WebSocket subscriptions for real-time order book updates and trade feeds. With typed request and response structures, comprehensive error handling, and context-aware API calls, go-hyperliquid provides the idiomatic Go developer experience that the Hyperliquid ecosystem previously lacked, enabling the large Go trading infrastructure community to build on Hyperliquid. The SDK has active contributors and is maintained alongside the official Python and Rust SDKs.

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Katoshi logo

Katoshi

Katoshi is the premier trading automation engine built exclusively for Hyperliquid, enabling traders to build, deploy, and manage algorithmic strategies with millisecond precision and zero downtime. Trusted by thousands of active traders, Katoshi abstracts the complexity of algorithmic execution into an accessible platform that requires no deep coding expertise. At its core, Katoshi offers a complete automation toolkit: receive signals from TradingView, fire webhooks and custom API triggers, or deploy fully autonomous AI trading agents that react to market conditions in real-time. The platform also supports MCP (Model Context Protocol) integrations, putting cutting-edge AI-driven execution within reach of any trader. Katoshi's deep native integration with Hyperliquid means bots can tap directly into one of crypto's fastest and most liquid on-chain order books, accessing perpetuals across hundreds of markets with minimal slippage. Whether automating a simple RSI crossover strategy or running a multi-leg algorithmic portfolio, Katoshi provides reliable infrastructure to scale it. Built from the ground up for Hyperliquid's architecture, it has become the go-to automation layer for retail traders and institutional desks operating in the ecosystem.

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Feature Comparison

Featurego-hyperliquidKatoshi logoKatoshi
LayerMulti-LayerHyperCore
CategorySDKs & Developer ToolsTrading Bots & Automation
StatusActiveActive
Launch Year2025
Websitegithub.comkatoshi.ai
Twitter@KatoshiAI
GitHubNot publicNot public
VerifiedUnverifiedUnverified
Tags
AIautomationtrading-agentsnon-custodial

Score Comparison

go-hyperliquidKatoshi
Open Source
go-hyperliquid
Not public
Katoshi
Not public
Verified
go-hyperliquid
Unverified
Katoshi
Unverified
Ecosystem Breadth
go-hyperliquid
0 tags
Katoshi
4 tags
Maturity
go-hyperliquid
Unknown
Katoshi
Since 2025

Feature Matrix

Featurego-hyperliquidKatoshi logoKatoshi
Open Source
Verified
Has Website
Has Twitter
Has GitHub
Active Status

Key Differences

Layer Architecture

go-hyperliquid operates on Multi-Layer (spans multiple hyperliquid layers), while Katoshi runs on HyperCore (native on-chain perpetual orderbook). This affects composability, transaction speed, and the types of integrations each protocol supports.

Category Focus

go-hyperliquid is focused on sdks & developer tools, while Katoshi targets trading bots & automation. They serve different user needs within the Hyperliquid ecosystem.

When to Use Each

Choose go-hyperliquid if you...

  • Want a sdks & developer tools solution on Multi-Layer
  • Need: Community Golang SDK for the Hyperliquid API with concurrent streaming support

Choose Katoshi if you...

  • Want a trading bots & automation solution on HyperCore
  • Need features like AI and automation
  • Need: AI-powered trading automation engine built exclusively for Hyperliquid

Ecosystem Integration

go-hyperliquid

go-hyperliquid operates on Multi-Layer (spans multiple hyperliquid layers). Spanning multiple layers lets it combine the strengths of each, though integration complexity is higher.

Katoshi logo

Katoshi

Katoshi operates on HyperCore (native on-chain perpetual orderbook). Running on HyperCore gives it direct access to the native orderbook with minimal latency and maximum throughput.

Community Verdict

Which do you prefer?

Share your experience with go-hyperliquid or Katoshi to help others in the Hyperliquid community make better decisions.

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