1. Hypaw Terminal
Hypaw Terminal is a platform built on top of Hyperliquid that allows users to create, configure, and deploy strategy agents — without writing code.
Each agent listens to real-time data (called context) and responds with actions like publishing a post, executing a trade, or flagging a signal. All logic in the system is powered by the Model Context Protocol (MCP) — a standard that feeds structured data from multiple sources directly into agent logic.
Terminal is designed for traders, analysts, and ecosystem participants who want to automate decisions based on live market activity, social signals, and wallet movements — with full control over how and when the agent acts.
Agents
Agents are rule-based strategies that continuously evaluate context and trigger defined actions. They are fully onchain-aware and can be linked directly to Hyperliquid for execution.
Each agent type has a specific purpose — for example:
A Social Agent may automatically post to X (Twitter) when a token trends.
A Whale Watcher Agent may flag when large wallets shift tokens.
A Tech/Market Agent may detect breakouts and notify or act.
You select the type, configure the triggers, and the agent runs automatically.
MCP: The Model Context Protocol
The Model Context Protocol (MCP) is the core infrastructure that powers agents inside Hypaw Terminal. It standardizes how external data — social, market, and onchain — is ingested, normalized, and delivered in real time to every active agent.
MCP eliminates the need for manual scraping, indexing, or data interpretation. Instead, it provides a live, queryable context stream that agents subscribe to and respond to.
What MCP Does
MCP acts as the middleware between raw data sources and agent logic. It performs three key functions:
Ingestion MCP connects to external sources and continuously pulls live signals. These include:
Social signals from X (Twitter), Discord, and Telegram
Market feeds such as price, volume, volatility, momentum, and order book data
Onchain data like wallet transfers, governance votes, DAO activity, and LP changes
Normalization Each signal is transformed into a standard format that agents can understand — regardless of its origin. This avoids the need for custom data parsers, API wrappers, or unstructured processing.
Context Delivery Once normalized, the data is routed to agents as a real-time stream. Every agent subscribes only to the types of context it needs (defined at configuration), which keeps performance tight and logic clean.
Examples of Context from MCP
X (Twitter)
Mention count, sentiment, influencer cluster
Trigger alert if $TOKEN gets 1000+ mentions/hour
Telegram
Keyword frequency, user activity
Post to X if community hype surges on a project
Price Feeds
OHLCV data, volatility, breakouts
Execute long/short trades based on technical patterns
Wallet Tracking
Transfer size, wallet tags, source/destination
Follow whale moves or smart contract activity
DAO Proposals
Vote status, proposer, impact scope
Alert if a treasury change is about to pass
Agents can mix multiple types of context into a single logic graph — e.g., a trade trigger based on both sentiment and price momentum, or a content strategy driven by Telegram traffic and DAO updates.
Agent Integration
When you create an agent in Terminal, you define its context dependencies — the types of data it needs to watch.
For example:
A Social Agent might request:
X_mentions,telegram_hype,market_capA Whale Watcher might request:
wallet_transfers,token_price,liquidity_events
MCP ensures that only the requested streams are routed to that agent, keeping compute costs low and execution focused.
📖 Learn more at https://modelcontextprotocol.io
Supported Integrations
Hypaw Terminal is designed to connect agent logic directly to real execution environments and publishing endpoints. Out of the box, it supports two primary integrations:
Hyperliquid
Terminal runs natively on Hyperliquid, a high-performance, onchain perpetual futures exchange.
Agent actions can trigger execution logic such as:
Opening or closing positions
Placing limit or market orders
Setting stop-loss or take-profit levels
Monitoring price thresholds, volatility, or momentum signals
Execution is non-custodial. You approve access through your connected wallet and set limits for each agent’s trading scope. The platform ensures strategies are sandboxed and rate-limited, and you can stop or pause any agent at any time.
Hyperliquid also powers real-time market context — including price feeds, volume, open interest, and funding rates — which are delivered via MCP.
Twitter (X)
Agents can be configured to publish posts to X (formerly Twitter), allowing for automated content strategies based on real-time activity.
Example use cases:
Automatically publish when a token trends on Telegram
Highlight market shifts or DAO outcomes in real time
Post trading alerts, memes, or summary content without manual effort
Each Social Agent includes post templating and frequency controls. Posting requires X account auth, and content is published through the official API.
Coming Soon
Future integrations will include:
Telegram (bot output + context ingestion)
Discord (posting and signal routing)
Arweave / Lens / Farcaster (for Web3-native content publishing)
Cross-chain DEXs and vault protocols for DeFi agents
Custom webhook endpoints for routing output to your own infra
You’ll be able to use Terminal as a signal layer, execution engine, or both — all configured from the same interface.
Next: 2. Agent Types → Explore the agents available in Terminal and how each one works.
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