BetBuilders AI

BetBuilders AI brings model-based football and Swedish ice hockey analysis into your AI.

Ask about a match to get the model's win, draw and loss probabilities (hockey: after 60 minutes and including overtime), expected goals, the most likely scores and the distribution of total goals. Read the match analysis with recent form, each team's xG trend over the last ten games, table position, KPIs with league ranks and key players.

MCP connector

Server URL: https://www.betbuilders.ai/mcp
Login: None
Protocol: MCP 2026-07-28
Instructions: BetBuilders AI (betbuilders.ai) publishes model-based match predictions, a Monte Carlo match simulator and match/team statistics for football (40 leagues, e.g. Premier League, La Liga, Bundesliga, Serie A, Ligue 1, Champions League, Allsvenskan, Eliteserien) and Swedish ice hockey (SHL and HockeyAllsvenskan).
How to use the tools:
Start with when the user names teams or a league but you have no match_id. Most other tools also accept "teams" directly.
: the model's probabilities (match result, expected goals, scorelines, goal totals) plus outcome ids for .
: the written match analysis, form, xG form curve with trend, league-table context, key players.
: one team's season statistics, KPIs with league ranks, xG form curve and recent results.
: what-if scenarios (player out, goalie change, team level, neutral venue) compared with the baseline.
: the joint probability of several outcomes in the same match, using outcome ids from .

Tools

Reads data9

Skills

None in the store listings or on the server

MCP connector

Server URL

https://www.betbuilders.ai/mcp

None

Protocol

MCP 2026-07-28

Instructions

BetBuilders AI (betbuilders.ai) publishes model-based match predictions, a Monte Carlo match simulator and match/team statistics for football (40 leagues, e.g. Premier League, La Liga, Bundesliga, Serie A, Ligue 1, Champions League, Allsvenskan, Eliteserien) and Swedish ice hockey (SHL and HockeyAllsvenskan).

How to use the tools:

Start with when the user names teams or a league but you have no match_id. Most other tools also accept "teams" directly.

: the model's probabilities (match result, expected goals, scorelines, goal totals) plus outcome ids for .

: the written match analysis, form, xG form curve with trend, league-table context, key players.

: one team's season statistics, KPIs with league ranks, xG form curve and recent results.

: what-if scenarios (player out, goalie change, team level, neutral venue) compared with the baseline.

: the joint probability of several outcomes in the same match, using outcome ids from .