Polymarket Bot Analyst
БесплатноНе проверенMCP server for analyzing successful trading bots on Polymarket, enabling discovery of top traders, AI-powered strategy classification, and bot detection.
Описание
MCP server for analyzing successful trading bots on Polymarket, enabling discovery of top traders, AI-powered strategy classification, and bot detection.
README
MCP server for analyzing successful trading bots on Polymarket — discover top traders, classify their strategies with AI, and detect bots on the world's largest prediction market.
TypeScript MCP Node.js CI Release
📋 Table of Contents
- Overview
- Architecture
- Tools
- Getting Started
- Connect to Claude Desktop
- Run the Test Suite
- Project Structure
- Configuration
Overview
This project implements a Model Context Protocol (MCP) server that exposes three powerful tools for analyzing trading activity on Polymarket. It combines real-time leaderboard data from Polymarket's Data API with LLM-powered strategy classification via OpenAI.
Key Features
- 🏆 Top Trader Discovery — Fetch leaderboard rankings by timeframe
- 🧠 AI Strategy Analysis — Classify strategies (arbitrage, market-making, etc.) using GPT-4o-mini
- 🤖 Bot Detection — Heuristic + LLM-based identification of automated traders
- 📊 Batch Reporting — Concurrent analysis of multiple profiles
- 🔄 Resilient API Layer — Exponential backoff, rate-limit handling (429 + Retry-After), graceful fallbacks
graph TD
subgraph Client ["Client Layer"]
MCP_Client["MCP Client (e.g., Claude Desktop)"]
end
subgraph Server ["MCP Server Layer"]
index["index.ts (McpServer)"]
Validation["Zod Validation"]
end
subgraph Tools ["Tool Handlers"]
Traders["traders.ts (find_top_traders)"]
Analysis["analysis.ts (analyze_trader_strategy)"]
Reports["reports.ts (generate_batch_report)"]
end
subgraph Services ["External Services & Utils"]
PAPI["api/polymarket.ts (Polymarket Data API)"]
LLM["utils/llm.ts (OpenAI GPT-4o-mini)"]
end
MCP_Client -- "stdio (JSON-RPC)" --> index
index --> Validation
Validation --> Traders
Validation --> Analysis
Validation --> Reports
Traders --> PAPI
Analysis --> PAPI
Analysis --> LLM
Reports --> Analysis
Reports --> PAPI
style Client fill:#f9f,stroke:#333,stroke-width:2px
style Server fill:#bbf,stroke:#333,stroke-width:2px
style Tools fill:#dfd,stroke:#333,stroke-width:2px
style Services fill:#ffd,stroke:#333,stroke-width:2px
Tool Execution Flow
sequenceDiagram
participant C as MCP Client
participant S as MCP Server
participant T as Tool Handler
participant P as Polymarket API
participant L as OpenAI LLM
C->>S: Call "analyze_trader_strategy"
S->>S: Validate Input (Zod)
S->>T: handleAnalyzeStrategy(profile_id)
T->>P: Fetch Profile Data & PnL
P-->>T: User Data
T->>P: Fetch Trade History
P-->>T: Trade History
T->>L: Classify strategy (history)
L-->>T: strategy_analysis (JSON)
T-->>S: strategy_result
S-->>C: Tool Response (JSON)
Tools
1. find_top_traders
Fetch top-performing traders from the Polymarket leaderboard with bot detection.
| Parameter | Type | Description |
|---|---|---|
limit |
integer | Number of traders (1–50) |
timeframe |
string | "7d", "30d", or "all_time" |
Output: Array<{ profile_id, pnl, is_bot }>
2. analyze_trader_strategy
Deep-dive analysis of a single trader using trade history + LLM classification.
| Parameter | Type | Description |
|---|---|---|
profile_id |
string | Wallet address (0x…) or username (@name) |
Output: { strategy_description, risk_level, risk_justification, success_score, is_bot }
3. generate_batch_report
Concurrent analysis of multiple profiles with error-resilient execution.
| Parameter | Type | Description |
|---|---|---|
profile_ids |
string[] | Array of profile IDs (1–50) |
Output: Array<{ profile_id, pnl, strategy_description, risk_level, risk_justification, success_score, is_bot }>
Getting Started
Prerequisites
- Node.js ≥ 22
- npm ≥ 10
- OpenAI API key (for strategy analysis)
Installation
# Clone the repository
git clone <your-repo-url>
cd polymarket-mcp-bot-analyst
# Install dependencies
npm install
# Configure environment
cp .env.example .env
# Edit .env and add your OPENAI_API_KEY
Build & Run
# Build TypeScript
npm run build
# Start the MCP server (stdio transport)
npm start
# Or run directly with tsx (development)
npm run dev
Connect to Claude Desktop
Add this server to your Claude Desktop configuration:
macOS
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"polymarket-bot-analyst": {
"command": "node",
"args": ["/absolute/path/to/polymarket-mcp-bot-analyst/dist/index.js"],
"env": {
"OPENAI_API_KEY": "sk-..."
}
}
}
}
Windows
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"polymarket-bot-analyst": {
"command": "node",
"args": ["C:\\path\\to\\polymarket-mcp-bot-analyst\\dist\\index.js"],
"env": {
"OPENAI_API_KEY": "sk-..."
}
}
}
}
After saving, restart Claude Desktop. The three tools will appear in the tools menu (🔨 icon).
Run the Test Suite
The test runner executes all three tools against the live Polymarket API and generates the required JSON artifacts:
npm run test:run
This produces:
| File | Description |
|---|---|
test_run.json |
Full execution log with data for 3+ traders |
performance_report.json |
Latency metrics for each endpoint |
my_report.json |
Architectural description of each endpoint |
Project Structure
polymarket-mcp-bot-analyst/
├── src/
│ ├── index.ts # MCP server entry point
│ ├── types.ts # Shared interfaces & config
│ ├── api/
│ │ └── polymarket.ts # Polymarket Data API wrapper
│ ├── tools/
│ │ ├── traders.ts # find_top_traders handler
│ │ ├── analysis.ts # analyze_trader_strategy handler
│ │ └── reports.ts # generate_batch_report handler
│ ├── utils/
│ │ └── llm.ts # OpenAI LLM integration
│ └── test-run.ts # Artifact generator script
├── test_run.json # Generated test run log
├── performance_report.json # Generated latency metrics
├── my_report.json # Generated architecture report
├── package.json
├── tsconfig.json
├── .env.example
└── .gitignore
Configuration
| Environment Variable | Required | Description |
|---|---|---|
OPENAI_API_KEY |
Yes | OpenAI API key for GPT-4o-mini |
Internal Constants (in src/types.ts)
| Constant | Default | Description |
|---|---|---|
POLYMARKET_API_BASE |
https://data-api.polymarket.com |
API base URL |
REQUEST_TIMEOUT_MS |
15000 |
HTTP request timeout |
MAX_RETRIES |
3 |
Max retry attempts per request |
RETRY_BASE_DELAY_MS |
1000 |
Base delay for exponential backoff |
BOT_TRADE_THRESHOLD |
200 |
Min trades to flag as bot |
BOT_TRADES_PER_HOUR_THRESHOLD |
10 |
Min trades/hour for bot flag |
License
MIT
Установка Polymarket Bot Analyst
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/DzimaSh/polymarket-mcp-bot-analystFAQ
Polymarket Bot Analyst MCP бесплатный?
Да, Polymarket Bot Analyst MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Polymarket Bot Analyst?
Нет, Polymarket Bot Analyst работает без API-ключей и переменных окружения.
Polymarket Bot Analyst — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Polymarket Bot Analyst в Claude Desktop, Claude Code или Cursor?
Открой Polymarket Bot Analyst на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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