HPSILab Quant finance MCP for US stocks, ETFs, options, Monte Carlo, backtesting, and risk analysis.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
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 Β· Pricing Β· Tool reference Β· Client setup Β· Python SDK
| Registry name | io.github.haiyunsky/hpsilab-quant-finance-mcp |
| Version | 0.10.0 β a source checkout reports 0.10.0+source |
| Transports | Streamable HTTP (hosted) Β· stdio (PyPI package) |
| Remote endpoint | https://hpsilab.com/mcp |
| Package | pip install -U hpsilab-quant-finance-mcp |
| Authentication | Bearer API key, or HPSILAB_API_KEY for stdio |
| Tools | 10 β nine financial research tools plus register_account |
Recommended, and requires no local installation.
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.
All financial research tools require a valid API key. See authentication for key handling and rotation.
For clients that require a local process:
This example uses the mcpServers schema supported by Claude and Cursor; VS
Code and GitHub Copilot use a servers schema instead.
Then verify it through the MCP client:
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.
Nine financial research tools, plus register_account. Tool names and parameter
meanings are part of the public compatibility contract.
| Tool | What it returns | Behavior |
|---|---|---|
analyze_stock | Aggregate directional and quantitative stock analysis | Read-only |
get_ai_prediction | Next-session prediction, confidence, and model consensus | Read-only |
get_iv_radar | IV level, rank, percentile, skew, and regime | Read-only |
get_option_pressure | Max pain, gamma walls, expected move, and pressure zones | Read-only |
get_monte_carlo | 30-day simulated distribution and probabilities | Read-only |
get_equity_curve | Strategy backtests and risk-adjusted performance | Read-only |
get_pretrade_risk_scan | Position, exposure, correlation, and risk checks | Read-only |
generate_stock_images | Hosted stock and options chart artifacts | Creates an artifact; not idempotent |
generate_stock_research_report | Structured Markdown research report and timestamp | Creates an artifact; not idempotent |
register_account | Account credentials for the authenticated caller | Creates 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.

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.
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.
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_code | Meaning | What resolves it |
|---|---|---|
api_key_required | No key is configured | Registering. Nothing is sent downstream |
rate_limited | Calling too fast (429) | Waiting β next_actions carries the seconds |
insufficient_credits | The Credit balance is empty (402) | Adding Credits, or registering for trial Credits |
allowance_exhausted | The free evaluation ceiling is spent (402) | Registering, or verifying an email. Money does not lift it |
settlement_unknown | A payment whose outcome is unconfirmed | Reconciliation. 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:
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 β 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.
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.
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.
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