hxsteric/mercury
Mercury — Blockchain Cash Flow Analyzer | Hermes Agent Skill for multi-chain analysis, fraud detection, trading strategy & interactive WebGL dashboard
Mercury is a blockchain cash flow analyzer and Hermes Agent skill designed to provide transparency into wallet activities across Ethereum, Base, and Solana. It utilizes parallel subagents to fetch transaction data, identify six specific fraud patterns, and generate AI-driven trading strategies based on wallet behavior. The project features a multi-layer WebGL and Canvas dashboard for real-time visualization of inflows, outflows, and risk metrics. It operates as a standalone tool or an integrated Hermes skill for automated multi-chain investigations.
- Analyzes transaction flows across Ethereum, Base, and Solana chains
- Detects six fraud patterns including mixer interactions and dust attacks
- Visualizes data via interactive WebGL and Canvas-based dashboards
full readme from github
Mercury — Blockchain Cash Flow Analyzer
A Hermes Agent skill for multi-chain blockchain cash flow analysis, fraud detection, trading strategy generation, and real-time interactive dashboards.
Features
- Multi-Chain Support — Ethereum, Base, and Solana transaction fetching
- Cash Flow Analysis — Period-by-period inflow/outflow breakdown, token distribution, top counterparties
- Fraud Detection — 6 pattern detectors (dust attacks, rapid transfers, mixer interaction, address poisoning, dormant activation, high fan-out)
- Trading Strategy — AI-generated trading insights based on wallet behavior patterns
- Interactive Dashboard — Three-layer WebGL + Canvas + HTML dashboard with:
- SpectraNoise-inspired neural network noise background
- Live network particle animation with mouse interaction
- v0-style stat cards, gauges, charts, and risk grid
- Hermes Subagents — Parallel execution with
delegate_taskfor maximum speed
Installation
Quick Install (for Hermes Agent users)
# Clone into your Hermes skills directory
git clone https://github.com/YOUR_USERNAME/mercury.git ~/.hermes/skills/data-science/blockchain-cashflow
API Keys
Add your API keys to ~/.hermes/.env:
ETHERSCAN_API_KEY=your_etherscan_key # Free at https://etherscan.io/apis
BASESCAN_API_KEY=your_basescan_key # Free at https://basescan.org/apis
HELIUS_API_KEY=your_helius_key # Free at https://helius.dev
The scripts auto-load keys from ~/.hermes/.env — no manual export needed.
Usage
With Hermes Agent (Recommended)
Just tell your Hermes agent:
Analyze wallet 0x8a4ff766a5dfb16d9dbd6a31f950c48a0caf0f54
The agent will automatically:
- Detect the chain (Ethereum/Base/Solana)
- Fetch all transactions using parallel subagents
- Run cash flow analysis + fraud detection simultaneously
- Generate a trading strategy
- Launch the interactive dashboard
Standalone Scripts
# 1. Fetch transactions
python3 scripts/fetch_transactions.py \
--address 0x8a4ff766a5dfb16d9dbd6a31f950c48a0caf0f54 \
--chain ethereum \
--include-tokens \
--output /tmp/bc_txns.json
# 2. Analyze cash flow
python3 scripts/cashflow_analyzer.py \
--input /tmp/bc_txns.json \
--address 0x8a4ff766a5dfb16d9dbd6a31f950c48a0caf0f54 \
--output /tmp/bc_cashflow.json
# 3. Detect fraud patterns
python3 scripts/fraud_detector.py \
--input /tmp/bc_txns.json \
--address 0x8a4ff766a5dfb16d9dbd6a31f950c48a0caf0f54 \
--output /tmp/bc_fraud.json
# 4. Generate trading strategy
python3 scripts/trading_strategy.py \
--cashflow /tmp/bc_cashflow.json \
--fraud /tmp/bc_fraud.json \
--output /tmp/bc_strategy.json
# 5. Launch dashboard
python3 scripts/dashboard_server.py \
--cashflow /tmp/bc_cashflow.json \
--fraud /tmp/bc_fraud.json
Architecture
Mercury Skill
├── SKILL.md # Hermes skill definition (YAML frontmatter + instructions)
├── scripts/
│ ├── fetch_transactions.py # Multi-chain transaction fetcher (Etherscan V2 / Helius)
│ ├── cashflow_analyzer.py # Period-by-period cash flow analysis
│ ├── fraud_detector.py # 6-pattern fraud detection engine
│ ├── trading_strategy.py # Trading strategy generator
│ ├── visualizer.py # Terminal-based ASCII visualization
│ ├── dashboard_server.py # Python HTTP server for the dashboard
│ └── dashboard.html # Three-layer interactive dashboard
└── README.md
Dashboard Preview
The dashboard features three animation layers:
- Layer 0: WebGL fragment shader with fbm noise, domain warping, scanlines, and film grain
- Layer 1: Canvas 2D network particles with proximity connections and mouse attraction
- Layer 2: Dashboard UI with stat cards, flow network map, circular gauges, charts, and risk grid
Fraud Detection Patterns
| Pattern | Severity | Description |
|---|---|---|
| Dust Attacks | Medium | Tiny unsolicited token transfers |
| Rapid Transfers | Medium | Burst activity suggesting bots or wash trading |
| Mixer Interaction | Critical | Transfers to/from known mixing services |
| Address Poisoning | High | Dust from addresses mimicking legitimate ones |
| Dormant Activation | Medium | Long-inactive wallet suddenly active |
| High Fan-Out | High | Single-block mass distribution |
Requirements
- Python 3.8+
- No external dependencies (stdlib only!)
- Hermes Agent (for subagent orchestration)
License
MIT
Credits
Built for the Nous Research Hermes Agent Hackathon — March 2026