Connect-MCP

HPSILab Quant Finance

io.github.haiyunsky/hpsilab-quant-finance-mcp · v0.11.0

HPSILab Quant finance MCP for US stocks, ETFs, options, Monte Carlo, backtesting, and risk analysis.

MCPremotelocal · pypiAPI keyFinanceResearch & educationImages, video & audio

Reported outcomes

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Last check

Reachable, 10 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 66/100

What it does: 10 tools · 7 read, 3 write · Finance, Email, Research & education

Test call get_equity_curve: failed — tool error: Not authenticated (726 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +6
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: 0
  • Read/write annotations: +5
  • Safe test call: 0
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://hpsilab.com/mcp
Package
registry:   pypi
identifier: hpsilab-quant-finance-mcp
version:    0.11.0
transport:  stdio

Tools

10 tools listed at last check
  • register_account Register a free hpsilab account for yourself, with no human involvement, and receive an API key immediately. Call this when the user has no API key yet and asks to sign up from here, or when a refusal's `next_actions` names register_account and the user agrees. This is the only tool
  • get_iv_radar Implied-volatility (IV) structure for a stock: how expensive options are, whether volatility is being squeezed, and whether traders are paying up for upside (calls) or downside (puts). Available to all signed-in users. Args: ticker: Stock symbol, e.g. "NVDA". refresh: By
  • get_monte_carlo Monte Carlo price simulation for the next ~10 trading days: thousands of random price paths estimate a likely price range and the odds of finishing higher. Args: ticker: Stock symbol, e.g. "AAPL".
  • get_ai_prediction AI next-day prediction: probability the stock closes UP, a paper-trading buy/watch/sell lean (research only, not a trade instruction), and how strongly the models agree (consensus). Available to every authenticated plan (Free / Pro / Enterprise); subject to the caller's plan request
  • get_equity_curve Backtest performance of the quant strategy across your watchlist: Sharpe ratio, max drawdown, win rate and total return per symbol. Available to every authenticated plan (Free / Pro / Enterprise); subject to the caller's plan requests/day and requests/minute limits. Args: t
  • get_option_pressure Option-chain pressure map for the nearest weekly/monthly expiry — Max Pain, dealer Gamma Wall, likely weekly high, and an extreme squeeze target. Args: ticker: Stock symbol, e.g. "SPY".
  • analyze_stock Aggregate all quant tools into one JSON stock analysis. The tool reuses the existing MCP tools as its data sources, then derives a direction signal, direction score, bullish factors, bearish factors and plain-English summary. If one underlying tool is gated, unavailable or raises an
  • get_pretrade_risk_scan Full pre-trade risk scan JSON for a stock. Pro tool ($0.15/call via x402 for anonymous callers; Credits for signed-in accounts). Signed-in hpsilab users (including Free, on its trial Credits) spend Credits from their balance at this tool's catalog price — each tool is priced differe
  • generate_stock_images Generate stock-report PNG images and return their URLs. This is intentionally separate from analyze_stock so the JSON analysis stays fast and light. The backend reuses the same Growth Engine image generators used by email/social publishing. Args: symbol: Stock symbol, e.g.
  • generate_stock_research_report Full markdown research report with five stock-report charts. Pro tool ($0.35/call via x402 for anonymous callers; free within plan limits for signed-in accounts, subject to a monthly report quota). Runs analyze_stock and stock-report image generation concurrently, then renders a pre

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