# app.oddsrail/polymarket-kalshi-trading

> app.oddsrail/polymarket-kalshi-trading — app-oddsrail-polymarket-kalshi-trading. Use this tool when you need to integrate cross-venue prediction markets into your AI workflow, enabling data-driven decision making with costed and attributed insights from Polymarket and Kalshi. It solves problems related to market analysis and prediction by providing a unified interface for multiple prediction markets. The tool accepts market data as input and outputs attributed predictions and costs, ideal for use cases requiring informed trading and risk assessment.

Canonical page: https://skillsregistry.net/skills/app-oddsrail-polymarket-kalshi-trading  
JSON: https://api.skillsregistry.net/v1/skills/app-oddsrail-polymarket-kalshi-trading

## Description

Cross-venue prediction markets for AI agents: Polymarket + Kalshi, costed and attributed

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 0.10.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/app.oddsrail%2Fpolymarket-kalshi-trading)
- **Repository:** <https://github.com/hmesutozsoy/oddsrail>

## Use it

MCP endpoint published by the skill: `https://mcp.oddsrail.app/mcp`

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": "app-oddsrail-polymarket-kalshi-trading"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/app-oddsrail-polymarket-kalshi-trading` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/app-oddsrail-polymarket-kalshi-trading/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