HPSILab Quant Finance MCP Server for Stock & Options Analytics

MCP serverCommerce & finance

Quantitative finance toolkit for US markets. Once added, your AI can pull data for US stocks, ETFs, and options, run Monte Carlo simulations, backtest strategies, and analyze risk.

Use HPSILab Quant Finance MCP Server for Stock & Options Analytics in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add HPSILab Quant Finance MCP Server for Stock & Options Analytics and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the register account tool from HPSILab Quant Finance MCP Server for Stock & Options Analytics

Details

Available today. Use it from your connected AI after setup.

Add it and ask your AI to analyze a stock or backtest a strategy. It works with US-listed securities.

HPSILab Quant Finance MCP Server for Stock & Options AnalyticsStart free

What your AI can do with it

  • Look up US stocks, ETFs, and options data
  • Run Monte Carlo simulations on portfolios or strategies
  • Backtest trading strategies against historical data
  • Analyze portfolio and strategy risk

Install HPSILab Quant Finance MCP Server for Stock & Options Analytics

The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http --scope user hpsilab-quant-finance-mcp-server 'https://hpsilab.com/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

    https://hpsilab.com/mcp

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=hpsilab-quant-finance-mcp-server&config=eyJ1cmwiOiJodHRwczovL2hwc2lsYWIuY29tL21jcCJ9

    Open the link and Cursor adds the server at that address.

  • ChatGPT

    https://hpsilab.com/mcp

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add hpsilab-quant-finance-mcp-server --url 'https://hpsilab.com/mcp'

    Run it once, then sign in with codex mcp login hpsilab-quant-finance-mcp-server if the server asks for an account.

From the project's README

As published by haiyunsky/hpsilab-quant-finance-mcp in README.md.

HPSILab is an open-source Python quantitative finance MCP server for research on US equities, ETFs, and supported options. It brings stock signals, implied volatility, options analytics, Monte Carlo simulation, AI prediction, backtesting, and risk analysis into ChatGPT, Claude, Cursor, VS Code, and other MCP clients. Connect once, ask in natural language, and receive structured results that an assistant can compare and explain.

Research and educational use only. HPSILab does not provide investment advice and does not execute trades.

Get a Free API Key · Pricing · Tool reference · Client setup · Python SDK

Registry nameio.github.haiyunsky/hpsilab-quant-finance-mcp
Version0.10.0 — a source checkout reports 0.10.0+source
TransportsStreamable HTTP (hosted) · stdio (PyPI package)
Remote endpointhttps://hpsilab.com/mcp
Packagepip install -U hpsilab-quant-finance-mcp
AuthenticationBearer API key, or HPSILAB_API_KEY for stdio
Tools10 — nine financial research tools plus register_account

Connect: hosted Streamable HTTP

Recommended, and requires no local installation.

  1. Register a free account, sign in, and generate an API key from Settings.
  2. Add the server to your client's private configuration, replacing hpsi_your_key. Never commit a real key or paste one into chat.

The example below is Claude Code's .mcp.json; other clients use different configuration schemas, all covered in client setup.

{
  "mcpServers": {
    "hpsilab": {
      "type": "http",
      "url": "https://hpsilab.com/mcp",
      "headers": {
        "Authorization": "Bearer hpsi_your_key"
      }
    }
  }
}
  1. Verify the connection:
Use HPSILab to analyze AAPL. Separate observed metrics from interpretation,
identify conflicting signals, and finish with a concise risk summary.

All financial research tools require a valid API key. See authentication for key handling and rotation.

Connect: local stdio

For clients that require a local process:

pip install -U hpsilab-quant-finance-mcp

This example uses the mcpServers schema supported by Claude and Cursor; VS Code and GitHub Copilot use a servers schema instead.

{
  "mcpServers": {
    "hpsilab": {
      "command": "hpsilab-quant-finance-mcp",
      "env": {
        "HPSILAB_API_KEY": "hpsi_your_key"
      }
    }
  }
}

Then verify it through the MCP client:

Use HPSILab to get the AI prediction for NVDA and summarize the model consensus.

The client discovers tools with MCP tools/list and invokes them with tools/call. See local setup and Python usage, which also covers calling the tool functions directly from Python.

Tools

Nine financial research tools, plus register_account. Tool names and parameter meanings are part of the public compatibility contract.

ToolWhat it returnsBehavior
analyze_stockAggregate directional and quantitative stock analysisRead-only
get_ai_predictionNext-session prediction, confidence, and model consensusRead-only
get_iv_radarIV level, rank, percentile, skew, and regimeRead-only
get_option_pressureMax pain, gamma walls, expected move, and pressure zonesRead-only
get_monte_carlo10-trading-day simulated distribution and probabilitiesRead-only
get_equity_curveStrategy backtests and risk-adjusted performanceRead-only
get_pretrade_risk_scanPosition, exposure, correlation, and risk checksRead-only
generate_stock_imagesHosted stock and options chart artifactsCreates an artifact; not idempotent
generate_stock_research_reportStructured Markdown research report and timestampCreates an artifact; not idempotent
register_accountAccount credentials for the authenticated callerCreates an account and sends email; not idempotent

Research tools accept one exchange ticker such as NVDA, SPY, or BRK.B; company names are not accepted. Live results can change between calls. Artifact tools can consume quota and should not be retried automatically.

Full inputs, outputs, side effects, and tool-selection guidance are in docs/tools.md.

Monte Carlo research example

Example visualization of scenario-based Monte Carlo research output. Results depend on the selected inputs and model assumptions. See get_monte_carlo for tool details.

Copy-ready prompts

Claude

Use HPSILab to analyze NVDA. Summarize the directional signal, AI model
consensus, IV regime, options pressure, 10-day Monte Carlo range, and the
three most important risks. Distinguish tool data from interpretation.

Cursor

Use HPSILab's IV radar and option-pressure tools for SPY. Compare IV rank,
percentile, skew, expected move, max pain, gamma wall, and pressure zones.
Return a compact table and do not recommend a trade.

ChatGPT

Run the HPSILab pre-trade risk scan for TSLA. Explain every warning or failed
check, preserve unavailable fields as unavailable, and quote the returned
reason instead of guessing. Do not execute or recommend a trade.

Setup guidance covers ChatGPT, Claude, Cursor, VS Code, GitHub Copilot, Continue, and Kimi. See the client setup guide for each client's transport and configuration format.

Errors, retries, and limits

Every failure is a structured object with a stable error_code, never prose an agent has to pattern-match. Five refusals matter, because each has a different remedy:

error_codeMeaningWhat resolves it
api_key_requiredNo key is configuredRegistering. Nothing is sent downstream
rate_limitedCalling too fast (429)Waiting — next_actions carries the seconds
insufficient_creditsThe Credit balance is empty (402)Adding Credits, or registering for trial Credits
allowance_exhaustedThe free evaluation ceiling is spent (402)Registering, or verifying an email. Money does not lift it
settlement_unknownA payment whose outcome is unconfirmedReconciliation. Do not retry it and do not pay again

Without a key the package stops locally, before constructing the downstream client or sending a request:

{
  "error": "api_key_required",
  "message": "A free API key is required.",
  "register_url": "https://hpsilab.com/register",
  "docs_url": "https://hpsilab.com/developer/v2"
}

401 and 402 responses are never retried. A 429 is retried only when it carries a valid Retry-After. Read-only calls use a finite retry budget for timeouts and recoverable 500/502/503/504 responses; artifact-producing calls are not retried automatically. The package also applies one process-local safeguard of 10 requests per rolling minute per API key — burst protection, not a quota, since only the hosted service knows the balance and the plan.

Field-by-field payloads, the Credits circuit breaker, and the reasoning behind each remedy are in docs/authentication.md and docs/python-sdk.md.

Why HPSILab

HPSILab gives assistants typed inputs, structured outputs, ticker validation, machine-readable errors, and dedicated tools instead of invented metrics. It supports US-listed equities, ETFs, and supported options data; coverage and limits depend on the hosted service and plan.

Safety and license

HPSILab is for research and education only. Outputs may be incomplete, delayed, or wrong and are not investment, financial, or trading advice. The MCP server has no brokerage connectivity, order entry, or trade-execution capability.

Licensed under the MIT License. Contributions are welcome; read AGENTS.md and CONTRIBUTING.md before proposing public schema changes.

Tools it offers (10)

What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.

  • register_account
  • get_iv_radar
  • get_monte_carlo
  • get_ai_prediction
  • get_equity_curve
  • get_option_pressure
  • analyze_stock
  • get_pretrade_risk_scan
  • generate_stock_images
  • generate_stock_research_report

Signals

GitHub stars
1
Last commit
Sep 2026
Advanced
Delivery
hpsilab-quant-finance-mcp MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-haiyunsky-hpsilab-quant-finance-mcp
Source
github.com/haiyunsky/hpsilab-quant-finance-mcp
Hosted endpoint
https://hpsilab.com/mcp