Skip to main content
Glama
Khavel

NBA Prop Lab MCP Server

by Khavel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Related Servers

Alternatives to NBA Prop Lab MCP Server

No user-submitted related servers found.

    Related Servers

    • NBA MCP Server

      SergioCastro02
      A
      license
      A
      quality
      B
      maintenance
      Enables MCP-compatible LLM clients to access live NBA data, including stats, standings, rosters, scores, and box scores via callable tools.
      9
      MIT

    • mcp-balldontlie

      pipeworx-io
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables querying basketball data including players, games, season averages, and stats from the balldontlie.io API.
      19 npm
      MIT

    • propzapi

      paperandbeyond23-gif
      A
      license
      Not graded
      quality
      B
      maintenance
      Props-first sports odds API with a hosted MCP server. Live odds and player props (moneyline, spreads, totals) across US sportsbooks, normalized to JSON. Tools: get_odds, get_props, get_events, get_books. API-key auth, free tier.
      MIT No Attribution

    • FBM

      quinjan
      A
      license
      B
      quality
      B
      maintenance
      Exposes 50 tools that let an existing AI agent act as a fantasy basketball general manager over a local deterministic engine, covering player valuation, projections, matchup simulations, lineup and IL planning, streaming, waivers, trades, and drafts. It returns insights, recommendations, and reviewer-checked proposals for the user to approve and execute in Yahoo themselves, without ever writing to the league.
      54
      MIT

    • sportsdataio

      pipeworx-io
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to query current sports injuries, player projections, and player prop betting markets across the NFL, NBA, MLB, NHL, CFB, and CBB via SportsDataIO's API.
      19 npm
      MIT

    • io.github.christianclaudio/esp

      christianclaudio
      A
      license
      B
      quality
      A
      maintenance
      Enables AI agents to query live and historical sports analytics, consensus betting odds, predictions, scores, schedules, standings, rosters, news, play-by-play, and win probabilities through structured tools and resources.
      33
      648 PyPI
      Apache 2.0
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.8/5.0

    Scored across 12 tools

    Disambiguation3/5

    While most tools have distinct purposes, there is notable overlap between proplab_track_record, proplab_backtest_summary, and proplab_backtest_by_rating, which all report historical hit rates and profit, and both track_record and backtest_by_rating provide rating-tier breakdowns. This could confuse agents selecting the right tool, though the descriptions help differentiate scope and auth requirements.

    Naming Consistency5/5

    All tools use the consistent `proplab_` prefix and snake_case with clear verb_noun or noun_noun patterns (e.g., proplab_search_players, proplab_backtest_summary). No deviations in convention.

    Tool Count5/5

    With 12 tools, the set is well-scoped for an NBA prop analytics server, covering games, picks, backtesting, and player research without excessive fragmentation or missing core areas.

    Completeness4/5

    The surface covers core workflows: game data, pick details, historical performance, backtesting, custom pick evaluation, and player research. Minor gap: no explicit tool to list all picks for a date (dashboard only shows top 10), but agents can work around via track_record or backtest tools.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources