# PredictionMarketsPicks Quant

> PredictionMarketsPicks Quant — predictionmarketspicks-mcp. Use this tool when you need to analyze and optimize prediction market trades, as it provides quant tools for calculating expected value, sizing bets, and identifying mispricing opportunities. It solves problems related to informed decision-making and risk management in prediction markets, particularly for Kalshi and Polymarket contracts. The tool accepts market data as input and outputs optimized trade recommendations, making it ideal for use in contexts where data-driven trading decisions are crucial.

Canonical page: https://skillsregistry.net/skills/predictionmarketspicks-mcp  
JSON: https://api.skillsregistry.net/v1/skills/predictionmarketspicks-mcp

## Description

Prediction-market quant tools — expected value, Kelly sizing, Bayesian updating, odds conversion, base-rate gaps, cross-platform arbitrage, and mispricing edge — for Kalshi and Polymarket contracts, exposed as a remote MCP server.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/cms27w01k3)
- **Repository:** <https://github.com/predictionmarketspicks/mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "predictionmarketspicks-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/predictionmarketspicks-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/predictionmarketspicks-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt