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HPSILab MCP
Options intelligence for AI agents — IV, Monte Carlo & more
8-tool MCP server for US equity options intelligence: real-time IV radar, Monte Carlo price simulation, options pressure maps, equity curve backtesting, and quantum ML prediction signals for AI-driven trading research.
Hey Product Hunt 👋
I'm Haiyun, the solo founder behind HPSILab.
The idea started simply: I was trading options and couldn't tell if the price I was seeing was fair. That led me to Black-Scholes, then IV surface modeling, then Monte Carlo simulation — and eventually to the question of why none of this was accessible outside a Bloomberg terminal.
The MCP angle came later. When I saw MCP emerging as the integration standard for AI agents, it clicked: options analytics shouldn't live in a dashboard. It should be callable — by your AI agent, in your coding environment, mid-conversation.
So I built it. 8 tools, one remote endpoint, live in production:
IV Radar — vol rank, percentile, risk reversal, regime
Options Pressure — max pain, gamma wall, expected move
Monte Carlo — 10,000-path simulation over 30 days
AI Prediction — ensemble signal (GBM + LSTM + quantum VQC)
Equity Curves — backtested Sharpe, Sortino, drawdown
Full Report — structured markdown research note
Try it free at hpsilab.com, or connect via MCP at https://hpsilab.com/mcp.
Happy to answer any questions — about the product, the quantum ML layer, or the math behind any of it.
About HPSILab MCP on Product Hunt
“Options intelligence for AI agents — IV, Monte Carlo & more”
HPSILab MCP was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #110 on the daily leaderboard. 8-tool MCP server for US equity options intelligence: real-time IV radar, Monte Carlo price simulation, options pressure maps, equity curve backtesting, and quantum ML prediction signals for AI-driven trading research.
On the analytics side, HPSILab MCP competes within Developer Tools, Artificial Intelligence and Finance — topics that collectively have 994.6k followers on Product Hunt. The dashboard above tracks how HPSILab MCP performed against the three products that launched closest to it on the same day.
Who hunted HPSILab MCP?
HPSILab MCP was hunted by hpsilab.com. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of HPSILab MCP including community comment highlights and product details, visit the product overview.
hpsilab.com