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    • A
      license
      Not graded
      quality
      D
      maintenance
      Real-time prediction market intelligence for AI agents. Query Polymarket and Kalshi markets, wallet profiles, smart money leaderboards, social pulse signals, price candlesticks, and orderbook data — 13 agents, one MCP connection. Powered by 1.1TB+ of historical data.
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables MCP-compatible assistants to research prediction markets on Polymarket and Kalshi, analyze public wallets, read market signals, and run paper-only trading simulations.
      10
      29 npm
      MIT
    • A
      license
      A
      quality
      D
      maintenance
      Prediction market probability oracle for AI agents. 26 tools across 500+ live markets from Kalshi and Polymarket. Cross-source arbitrage detection, structured TPF signals, Kelly Criterion sizing, agent performance tracking, and webhook alerts.
      9
      60 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      An MCP server and Python toolkit that provides AI agents with real-time tools for Polymarket prediction markets, including liquidity scanning, arbitrage detection, and slippage estimation. It also offers advanced wallet intelligence, portfolio risk calculation, and probabilistic reasoning to enhance market analysis and strategy.
      94 PyPI
      1
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables AI agents to discover and analyze prediction markets, execute trades, and manage positions on Polymarket via the Model Context Protocol.
      7
      36 npm
      20
      MIT
    • A
      license
      A
      quality
      F
      maintenance
      Provides prediction market intelligence, research, and strategy signals for platforms like Kalshi, Polymarket, and Robinhood. It enables AI assistants to perform market screening, arbitrage detection, and deep causal analysis to support informed trading decisions.
      27
      1
      MIT

    TDQS

    B3.1/5.0

    Scored across 42 tools

    Disambiguation4/5

    The venue prefixes (kalshi_ vs no prefix) and action nouns keep most tools distinct. Only mild overlaps exist—notably find_markets vs search_markets vs kalshi_search_markets, and my_positions vs get_positions—but the descriptions clarify when to use each. No tools are truly indistinguishable.

    Naming Consistency4/5

    Names are consistently lowercase snake_case and mostly follow a predictable venue_action_noun pattern, e.g. kalshi_place_order, get_orderbook, cancel_all_orders. A few noun-style names like server_info, builder_stats, and position_size break the verb-first feel, but there is no chaotic style mixing.

    Tool Count2/5

    42 tools is well beyond the 25+ threshold for 'too many' and feels heavy even for a two-venue trading platform. Many tools could be consolidated or grouped, such as search variants, position variants, and several signal/analysis utilities. The breadth is real, but the count creates selection overhead.

    Completeness4/5

    The toolkit is broad: market discovery, order placement/cancellation, balances/positions, paper trading, redemption, resolution checks, builder attribution, and cross-venue settlement audits are all covered. Minor gaps include Kalshi-specific order status/fill history and a dedicated Polymarket trade history tool, so agents may need to work around those edges.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues