Skip to main content
Glama
DzimaSh

Polymarket MCP Bot Analyst

by DzimaSh
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

🤖 Polymarket MCP Bot Analyst

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

Related MCP server: CryptoConduit-MCP

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

This server cannot be installed

F
license - not found
-
quality - not tested
D
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DzimaSh/polymarket-mcp-bot-analyst'

If you have feedback or need assistance with the MCP directory API, please join our Discord server