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    MCP server for the Pyon trading platform that lets AI agents search markets, generate research, build and edit node-graph strategies, run backtests, diagnose problems, and optimize parameters with 2-D sweeps.
    13
    12 npm
    4
    MIT
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    Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.
    7
    62 npm
    MIT
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    MCP server that exposes the Backtest360 backtesting engine API as tools, enabling AI agents to conversationally discover indicators, build and validate strategies, run backtests, and read results.
    14
    67 PyPI
    MIT
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    A stock backtesting engine MCP server that fetches stock data, validates and executes dynamic strategies, and generates backtest results and reports.
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    4
    MIT
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    Remote MCP server for the UNESCO Institute for Statistics (UIS): ~5,000 indicators on education, science/R&D, culture and communication by country, region and year — hosted, nothing to install, no API key, with source URL, data release, retrieval timestamp and licence on every answer.
    5
    695 npm
    1
    MIT
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    Enables agents to fetch real-time stock data like current price, day range, and volume via yfinance, with future support for backtesting and custom trading strategies.
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    Provides actionable financial intelligence tools for AI agents including insider buying signals, earnings IV plays, market pulse, stock analysis, and options strategies via free public data sources.
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    MIT
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    Enables local auditing of trading strategies through MCP checkers for point-in-time data provenance, pre-trade order validation, and regime-fragility testing, while deferring promotion verdicts to a hosted service.
    6
    MIT
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    Provides AI agents access to cryptocurrency derivatives analytics through 22 unified tools covering 80+ CoinGlass API endpoints. Enables analysis of open interest, funding rates, liquidations, whale positions, order book data, and market sentiment indicators with plan-aware feature gating.
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    The MCP server for AlphaForge — the agent-native quant CLI: write strategies in JSON, optimize with Optuna TPE, validate with walk-forward, export to TradingView Pine v6. This server lets your AI agent drive the whole pipeline over MCP.
    17
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    Apache 2.0
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    Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.
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    AGPL 3.0
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    Enables LLM-powered race engineers to compute Formula 1 pit-stop strategies from real session data, including tire degradation modeling, optimal pit windows, undercut/overcut simulation, and finish-position projection.
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    A Python MCP server for deterministic fuzzy text matching using RapidFuzz. It enables text normalization, string comparison, best-match ranking, duplicate grouping, and match explanation via configurable profiles and strategies.
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    Quantitative research MCP server that lets AI define strategies and uses MetaTrader 5's official Strategy Tester to execute backtests, managing experiments and results via tools like run_backtest, get_run, and compare_runs.
    18
    MIT
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    An MCP server that exposes the Jesse algorithmic trading framework's capabilities to LLM agents for backtesting, optimization, and risk analysis. It provides 32 specialized tools for managing trading strategies and performing comprehensive market simulations via the Jesse REST API.
    69
    23
    MIT