mcp server
HPSILab Quant Finance
HPSILab Quant finance MCP for US stocks, ETFs, options, Monte Carlo, backtesting, and risk analysis.
Description as published by the maintainer. Source
- version 0.8.10
- active
active — Most recent push to the repository was 2026-08-07.
What this server can do
10 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
analyze_stock(symbol, refresh)- 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 error, the remaining tools still contribute to the final result (status "partial"); if every underlying tool fails, the whole call fails (status "error", isError=True) instead of a misleadingly "successful" empty analysis. Args: symbol: Stock symbol, e.g. "NVDA". refresh: Request fresh IV Radar data instead of using the backend's fresh IV cache. Defaults to False. Required: symbol.
generate_stock_images(force, types, symbol)- 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. "RXRX". force: Regenerate images instead of using cached PNGs. Defaults to True so manually requested images reflect the latest available data. types: Optional subset of chart types. Allowed values are "ai_prediction", "iv_radar", "option_pressure", "monte_carlo", and "equity_curves". Omit to generate every chart type. Required: symbol.
generate_stock_research_report(symbol, refresh, force_images)- 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 presentation-ready markdown report (direction, direction score, bullish / bearish factors, source-tool status, and the five chart embeds). The markdown is returned for display and the same data is mirrored in structured JSON. Signed-in hpsilab users call this within their plan's free rate limits. Anonymous / tokenless agents pay per call via x402 (USDC on Base) when payments are enabled — send the x402 payment in the request _meta. Args: symbol: Stock symbol, e.g. "RXRX". refresh: Bypass the backend's fresh IV cache for the IV-driven modules. Defaults to False. force_images: Force a fresh image render instead of reusing the backend's image cache. Defaults to False. Required: symbol.
get_ai_prediction(ticker)- AI next-day prediction: probability the stock closes UP, a plain buy/watch/sell-lean signal, and how strongly the models agree (consensus). Available to every authenticated plan (Free / Pro / Enterprise); subject to the caller's plan requests/day and requests/minute limits. Args: ticker: Stock symbol, e.g. "TSLA". Required: ticker.
get_equity_curve(ticker)- 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: ticker: Optional symbol to show just one row, e.g. "SPY". Leave blank for all.
get_iv_radar(ticker, refresh)- 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: Bypass the backend's fresh IV cache and request the latest option-chain pull. Defaults to False. Required: ticker.
get_monte_carlo(ticker)- 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". Required: ticker.
get_option_pressure(ticker)- 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". Required: ticker.
get_pretrade_risk_scan(symbol)- Full pre-trade risk scan JSON for a stock. Pro tool ($0.15/call via x402 for anonymous callers; free within plan limits for signed-in accounts). Signed-in hpsilab users call this within their plan's free rate limits. Anonymous / tokenless agents pay per call via x402 (USDC on Base) when payments are enabled — send the x402 payment in the request _meta. Args: symbol: Stock symbol, e.g. "NVDA". Required: symbol.
register_account(email)- Register a free hpsilab account for yourself, with no human involvement, and receive an API key immediately. Call this when you are hitting anonymous daily limits and want a higher allowance. You do not need a password, a wallet, or a web browser. The account is bound to you server-side, so calls you make after this are metered as your account even though you cannot change your own Authorization header. Registering keeps the anonymous daily allowance until the email address is confirmed; confirming it unlocks the full Free plan. Ask the human you are working with to click the link in the email that will arrive. A valid user email address is required. Do not call this tool with an empty or fabricated email address. If the user's email is unavailable, ask the user to provide it before calling register_account. Args: email: The real user email address that will receive verification. Required: email.
Last successful function declaration observed on . Source: https://hpsilab.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://hpsilab.com/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 1 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-07 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 0.8.10 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-08-06 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-08-06 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 10 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | hpsilab.com | |
| mcp endpoint status | ok | The server listed 10 functions when asked. | as of probe | hpsilab.com |
Where to get it
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These share tags the maintainers applied themselves, such as backtesting, monte-carlo, quantitative-finance, algorithmic-trading. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai-agent, algorithmic-trading, backtesting, claude-mcp, cursor-mcp, financial-research, generate-stock-research-report, implied-volatility, mcp-server, model-context-protocol, monte-carlo, options-analytics, pretrade-risk-scan, python, quant-finance-mcp, quantitative-finance, stock-analysis.
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json