# QuantSpace

> The unified AI-native platform for quantitative finance professionals — QCA, QuantLab, QuantX

## Docs

- [Authentication](https://docs.quantspace.limex.pro/authentication.md): No authentication required — open access
- [Best Practices](https://docs.quantspace.limex.pro/best-practices.md): How the pipeline works and ready-made prompts for agent rules
- [All MCP Clients](https://docs.quantspace.limex.pro/clients/all-mcp-clients.md): Connect any MCP-compatible client to QuantSpace
- [Claude Code](https://docs.quantspace.limex.pro/clients/claude-code.md): Connect QuantSpace to Claude Code via MCP
- [Cursor](https://docs.quantspace.limex.pro/clients/cursor.md): Connect QuantSpace to Cursor via MCP
- [Where Research Meets Production](https://docs.quantspace.limex.pro/index.md): Quantspace is the unified AI-native platform designed for quantitative finance professionals — covering your entire workflow.
- [Introduction](https://docs.quantspace.limex.pro/introduction.md): QuantSpace — ML trading pipeline orchestrator
- [Pipeline](https://docs.quantspace.limex.pro/pipeline.md): End-to-end ML trading pipeline — stages, data flow, and blob naming conventions
- [QCA — Research-to-Code Infrastructure](https://docs.quantspace.limex.pro/qca/index.md): Convert academic papers into production-ready research pipelines with intelligent debugging. Validate and iterate on financial research in hours instead of weeks.
- [QuantX MCP Servers](https://docs.quantspace.limex.pro/quantx/index.md): Client-facing documentation for hosted quantitative MCP servers
- [QuantX Quickstart](https://docs.quantspace.limex.pro/quantx/quickstart.md): Connect to a hosted MCP server and run the first tool call
- [Dataloader Server](https://docs.quantspace.limex.pro/quantx/servers/dataloader/index.md): Market-data retrieval, TA-Lib indicators, and dataframe exports.
- [MCP Client Setup](https://docs.quantspace.limex.pro/quantx/servers/deployed/client-setup.md): Connect hosted MCP servers from Cursor, Claude Desktop, and generic streamable HTTP clients
- [MCP Server Catalog](https://docs.quantspace.limex.pro/quantx/servers/deployed/index.md): Hosted MCP endpoints, connection contracts, and server-specific tool references
- [Shared MCP Tools](https://docs.quantspace.limex.pro/quantx/servers/deployed/shared-tools.md): Common helper tools exposed by hosted MCP servers
- [EP Ratio Screener Server](https://docs.quantspace.limex.pro/quantx/servers/ep-ratio-screener/index.md): Fundamental stock screening based on earnings yield and balance-sheet quality.
- [Fama-French Replicate Server](https://docs.quantspace.limex.pro/quantx/servers/fama-french-replicate/index.md): Official and replicated Fama-French factors plus loadings and alpha estimation.
- [Jump Models Server](https://docs.quantspace.limex.pro/quantx/servers/jump-models/index.md): JumpModel and SparseJumpModel regime fitting, online prediction, and backtesting.
- [Parallax ExtremeHurst Server](https://docs.quantspace.limex.pro/quantx/servers/parallax-extreme-hurst/index.md): ExtremeHurst signal generation from OHLCV data.
- [Statistical Factor Models Server](https://docs.quantspace.limex.pro/quantx/servers/statistical-factor-models/index.md): Stock-Watson, complete-panel, and dynamic statistical factor extraction.
- [Volatility Scaling Lab Server](https://docs.quantspace.limex.pro/quantx/servers/volatility-scaling-lab/index.md): Volatility targeting, EWMA volatility, Monte Carlo bands, and risk diagnostics.
- [Wavelet Mean Reversion Server](https://docs.quantspace.limex.pro/quantx/servers/wavelet-mean-reversion/index.md): Wavelet-based mean reversion analysis for financial time series.
- [Quickstart](https://docs.quantspace.limex.pro/quickstart.md): Connect to QuantSpace and run your first pipeline in minutes
- [run_data_extraction](https://docs.quantspace.limex.pro/tools/data-extraction.md): Download OHLCV market data and save to blob storage
- [run_dl_job](https://docs.quantspace.limex.pro/tools/dl-job.md): Train a PyTorch neural network and generate price predictions
- [run_feature_worker](https://docs.quantspace.limex.pro/tools/feature-worker.md): Compute technical indicators from OHLCV data and save to blob storage
- [run_ml_job](https://docs.quantspace.limex.pro/tools/ml-job.md): Train a scikit-learn ML model and generate price predictions
- [run_plot_job](https://docs.quantspace.limex.pro/tools/plot-job.md): Render chart HTML from pipeline JSON output
- [run_po_job](https://docs.quantspace.limex.pro/tools/po-job.md): Optimize portfolio weights from ML/DL predictions
- [run_risk_job](https://docs.quantspace.limex.pro/tools/risk-job.md): Generate risk analytics artifacts from portfolio optimization output
- [run_st_job](https://docs.quantspace.limex.pro/tools/st-job.md): Generate stress test HTML report from portfolio optimization output
- [run_trading_job](https://docs.quantspace.limex.pro/tools/trading-job.md): Run a VectorBT backtesting simulation using portfolio weights

## OpenAPI Specs

- [openapi](https://docs.quantspace.limex.pro/api-reference/openapi.json)