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Add DepthSight (#427)
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@@ -183,6 +183,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
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- [AlgoVault](https://github.com/AlgoVaultLabs/crypto-quant-signal-mcp) - `TypeScript` - MCP server returning composite crypto trade verdicts (direction, confidence, regime) across 5 perpetual-futures venues, with cross-venue funding-rate arbitrage and an on-chain Merkle-verified track record. Free tier.
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- [alpha-forge-mcp](https://github.com/alforge-labs/alpha-forge-mcp) - `Python` - MCP server wrapping the AlphaForge CLI for AI-agent-native backtesting, Optuna TPE optimization, and walk-forward testing of trading strategies from Claude Desktop, Cursor, or Claude Code.
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- [capitalcom-cli](https://github.com/SimonTarara62/capitalcom-cli) - `Python` - Unofficial CLI and async SDK for the Capital.com broker API: market data, guarded order execution, and real-time streaming.
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- [DepthSight](https://github.com/depthsight-pro/depthsight) - `Python` `TypeScript` - Self-hosted visual algo-trading platform featuring a drag-and-drop strategy builder, an AI co-pilot, and integrated billing.
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- [Inalpha](https://github.com/mirror29/inalpha) - `Python` `TypeScript` - Conversational multi-agent quant framework where agents rank currently-effective factors for entry timing (time-series rank IC), write complete strategy code that passes sandboxed audit before backtesting, and evolve strategies under multi-objective fitness; every order requires machine approval and the LLM never has a direct order path.
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- [income-desk](https://github.com/nitinblue/income-desk) - `Python` - Systematic options trading intelligence for small accounts with desk-based portfolio management, pre-trade validation, and multi-broker consolidation.
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- [mx-trader-bridge](https://github.com/27dream/mx-trader-bridge) - `Python` - AI auto-trading bridge for East Money's miaoxiang (妙想) China A-share simulation platform; BYOK multi-LLM (OpenAI/DeepSeek/Moonshot/GLM/Qwen) decision brain → automated order placement via miaoxiang API, with daily cron review and weekly AI reflection.
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