# PropLine

> Use this tool when you need to optimize live sports betting with real-time odds comparison and player-prop analysis across multiple bookmakers. It solves problems of inefficient betting research and suboptimal wager placement by providing cross-book +EV (expected value) insights and graded player-prop resolution. Input includes live sports data, and output is actionable betting information across 13 books.

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

## Description

Live sports betting odds, cross-book +EV, and graded player-prop resolution across 13 books.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/t3ulduc1rj)
- **Repository:** <https://github.com/proplineapi/propline-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": "proplineapi-propline-mcp"
    }
  }
}
```

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