Sports Betting Mcp

io.github.seang1121由 GitHub 帳號 seang1121 發布v1.0.0更新於 Oct 24, 2026

AI sports betting picks, odds, injuries & line movement. 1,353+ picks, 59.6% win rate.

已驗證STDIO僅桌面金融資料與分析

概覽

AI 產生的概覽

讓 AI 助理取得 NBA、NHL、NCAAB 與 MLB 的運動博彩推薦、即時賠率、傷兵報告、盤口變動與模型表現資料。

可以做什麼
把 MCP 用戶端連接到運動博彩分析 API,提供約 12 個工具。工具涵蓋當日推薦與最佳推薦、待結算與已結算推薦、單場比賽的 12 代理分析、即時勝負盤/讓分/總分賠率、盤口變動與傷兵警示、依聯盟與投注類型劃分的勝率、模型統計、使用者排行榜,以及系統健康檢查。每次呼叫都回傳結構化資料,助理可據以排序、篩選或說明。
適用情境
當你希望助理抓取這四個聯盟的每日博彩推薦、賠率與市場訊號,或在採取行動前核對已公布的推薦戰績時使用。適合已經關注運動博彩、並希望在自己的 AI 用戶端內直接查看資料而非另開網站的使用者。
執行需求
以 Python 套件形式在本機執行(pip install sports-betting-mcp,需 Python 3.10+),透過 stdio 通訊,因此需要本機 Python 執行環境。需要在 SPORTS_BETTING_API_KEY 環境變數中提供 API 金鑰,金鑰向供應方網站取得。選用變數 SPORTS_BETTING_API_URL 可設定 API 基礎網址,預設指向本機位址。需要能連線至供應方的 API。
安裝前請注意
API 金鑰屬於憑證,透過 SPORTS_BETTING_API_KEY 環境變數傳入,請勿寫入共用設定。此伺服器提供的是博彩推薦與賠率,屬於賭博相關資訊,並非財務建議,據此下注可能損失金錢。部分端點可以記錄推薦或註冊 webhook,會向供應方服務寫入資料。預設 API 網址指向本機,必須改為供應方主機才能正常運作。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Sports Betting Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

sports-betting-mcp

The first MCP server for sports betting. Give any AI agent live access to picks, odds, game analysis, and performance tracking across NBA, NHL, NCAAB, and MLB.

[Status] [Python] [PyPI] [License] [MCP] [Sports]

mcp-name: io.github.seang1121/sports-betting-mcp

What It Does

Connects any MCP-compatible AI agent to a live sports betting analysis system. Every pick is logged before tip-off and resolved against final scores. Nothing is cherry-picked.

MetricValue
Sports CoveredNBA, NHL, NCAAB, MLB
Bet TypesMoneyline, Spread, Totals
Pick Source12-agent consensus model
Total Picks3,859+ resolved
Platform Users30
Tools12 MCP tools
AuthAPI key (X-API-Key header)

Results by Sport

SportPicksWinsWin Rate
NBA1,26776260.1%
NHL1,14865657.1%
NCAAB1,14954947.8%
MLB28310938.5% (launched Apr 2026)

All results are queryable in real-time via the get_win_rate tool. Numbers update after every game.


Quick Start

Install

bash
pip install sports-betting-mcp

Add to Your MCP Client

Drop this into your MCP config (Claude Desktop, Cursor, Windsurf, Claude Code, etc.):

json
{  "mcpServers": {    "sports-betting": {      "command": "sports-betting-mcp",      "env": {        "SPORTS_BETTING_API_URL": "https://sportsbettingaianalyzer.com",        "SPORTS_BETTING_API_KEY": "your_api_key"      }    }  }}

Environment Variables

VariableRequiredDescription
SPORTS_BETTING_API_KEYYesYour API key for authentication
SPORTS_BETTING_API_URLNoAPI base URL (defaults to http://localhost:5000)

Works With

Any client that supports the Model Context Protocol:

ClientStatus
Claude DesktopFully supported
CursorFully supported
WindsurfFully supported
Claude Code (CLI)Fully supported
Any MCP ClientFully supported via stdio transport

Available Tools

12 tools. Every call returns structured data that AI agents can reason over, display, or act on.

Picks & Analysis

ToolWhat It Does
get_todays_picksAll AI picks with confidence scores and edge breakdowns, filterable by sport
get_top_pickSingle highest-confidence pick of the day
get_pending_picksCurrently unresolved picks that are still in play
get_completed_picksRecently resolved picks with W/L results -- verify the track record
analyze_gameFull 12-agent analysis on any game: consensus pick + edge breakdown

Odds & Market Data

ToolWhat It Does
get_live_oddsLive moneyline, spread, and totals for today's games
get_alertsActive alerts from the multi-agent system (line moves, injury impacts)

Performance & Stats

ToolWhat It Does
get_win_rateWin rate with breakdown by sport and bet type
get_model_statsModel performance: total picks, last-20 win rate, confidence tier breakdown
get_leaderboardUser rankings by win rate
get_system_statusHealth check -- uptime, database, scheduler status

How the Analysis Works

Each game runs through a multi-agent pipeline:

  1. 12 specialized agents evaluate the game independently -- covering momentum, matchups, injuries, rest, travel, public betting percentages, sharp money indicators, historical trends, and more.
  2. A consensus engine synthesizes all 12 opinions into a single pick with a confidence score.
  3. Edge calculation compares the model's implied probability against the current market line.
  4. Picks are logged before tip-off and resolved against final scores. No retroactive edits.

The confidence score and edge breakdown are included in every pick response, so your AI agent can filter, rank, or explain the reasoning behind any recommendation.


Full API — 22 Endpoints

The API has two tiers: Free (any API key) and Pro (approved access).

Free Tier (available to all API key holders)

EndpointMethodWhat It Does
/xk/pGETToday's AI picks with confidence scores
/xk/o/{sport}GETLive odds from FanDuel/BetMGM
/xk/wGETWin rate breakdown by sport and bet type
/xk/iGETActive injury report from Covers.com
/xk/mGETSignificant line movement (sharp money signals)
/xk/gamesGETToday's full schedule with odds snapshot and AI pick flags
/xk/statsGETModel performance by sport, bet type, confidence tier
/xk/lbGETLeaderboard — AI vs human win rates
/xk/newsGETSports news feed from RSS sources
/xk/qGETCurrently pending (unresolved) picks

Pro Tier (requires approved access)

EndpointMethodWhat It Does
/xk/fullGETFull structured picks — complete edge breakdowns, positive/negative edges, reasoning, scorecard, opposing side with odds, line movement, quality flags
/xk/analyzePOSTOn-demand 12-agent analysis for any game — send team names, get full consensus
/xk/resultsGETResolved picks with W/L, actual scores, profit, top contributing edges
/xk/clvGETClosing Line Value analysis — did the line move in our favor?
/xk/searchGETSearch all picks by team name with W/L record
/xk/logPOSTLog a pick (supports flip flag, pick source tracking)
/xk/log/batchPOSTBatch log up to 20 picks with per-pick success/duplicate/error status
/xk/historyGETYour pick history — pending, resolved, win rate
/xk/slipPOSTGenerate Nimrod bet slip image
/xk/webhookPOST/GET/DELETERegister webhooks for pick events
/xk/fullGETIncludes fade/flip data for every pick — opposing side, line, odds

Pro Pick Payload

Every pick from /xk/full includes:

json
{  "ai_pick": "Lakers -5.5",  "ai_verdict": "STRONG BET",  "ai_probability": "65%",  "ai_reasoning": "Lakers defense ranks top 5, opponent on B2B...",  "edges": [13 individual edge factors],  "top_edges": [top 5 positive],  "negative_edges": [top 3 negative],  "scorecard": [3 model scores],  "fade_pick": "Celtics +5.5",  "fade_team": "Celtics",  "fade_odds": "+105",  "fade_note": "Betting AGAINST the AI — take Celtics +5.5",  "line_moved": true,  "flags": ["line_moved"],  "data_quality": "good"}

Pick Source Tracking (for learning)

When logging picks, include pick_source to track decision types:

  • model_agree — following the AI's pick
  • flip — fading/betting against the AI
  • manual_override — custom pick

This enables win rate comparison between model-agree vs flip picks over time.


API Authentication

Authenticate with X-API-Key header. Get a free key at sportsbettingaianalyzer.com. Pro access requires admin approval.


Tech Stack

ComponentTechnology
RuntimePython 3.10+
ProtocolMCP (Model Context Protocol)
Transportstdio
BuildHatchling
DistributionPyPI (sports-betting-mcp)
BackendFlask + SQLite
Analysis12-agent consensus pipeline
SportsNBA, NHL, NCAAB, MLB

Related Projects

License

MIT

來源:README.md,提交 e0fa825

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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