stoquant-mcp
Provides access to App Store alternative data such as ratings, reviews, and other metrics via the get_alt_signals tool.
Provides access to GitHub alternative data, including repository activity and other metrics, via the get_alt_signals tool.
Provides access to Google Trends data via the get_alt_data tool.
Provides access to Wikipedia page view statistics via the get_alt_data tool.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@stoquant-mcpShow me top conviction picks"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
stoquant-mcp
Model Context Protocol (MCP) server for StoQuant — gives Claude (and any MCP-compatible agent) direct, read-only access to StoQuant's quant signals, ML predictions, screening, ownership, and macro data.
Free to start. A free StoQuant API key runs the core tools (quotes, Q-Score, screeners, market regime) at 100 requests/day. Power removes the cap and unlocks the premium tools (ML, alt-data, insider clustering). Get a key at https://stoquant.com/account/api-keys.
Source & listings: GitHub · npm · Official MCP Registry (io.github.ohadf2015/stoquant-mcp) · Landing page
One-command install
npx -y stoquant-mcp installYou'll be prompted for your API key. The installer writes the right claude_desktop_config.json for your OS, backs up any existing config, then prints the next step.
After install, fully quit and relaunch Claude Desktop. Type list available tools to confirm the stoquant_* tools are loaded.
Manual install (alternative)
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"stoquant": {
"command": "npx",
"args": ["-y", "stoquant-mcp", "serve"],
"env": {
"STOQUANT_API_KEY": "sk_live_…"
}
}
}
}Config locations:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%/Claude/claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json
Related MCP server: Financial Modeling Prep MCP Server
Tools (48)
Category | Tools |
Prices |
|
Research |
|
Signals |
|
Discovery |
|
Screener |
|
Ownership |
|
Filings & News |
|
Social |
|
Catalysts |
|
Alt-data |
|
Macro |
|
All tools are read-only. No mutation, no portfolio changes, no order placement. Each tool is annotated readOnlyHint so agents know it is safe to call.
Two things to know
The Q-Score (
get_qscore) is the headline 0-100 composite, computed on sector-residualized returns (sector beta removed). Start here for "is this a good stock".The ML prediction (
get_ml_prediction) returns the probability of outperforming the S&P 500 over a horizon (classification: bull|bear) — it is not a buy/hold/sell rating.
Resources
The server exposes reference docs an agent can read on demand:
stoquant://glossary— what Q-Score, ML outperformance, regimes, and signal accuracy mean, plus unit conventions.stoquant://methodology— sector residualization, IC-weighting, ML health gating, and screener field semantics.
Prompts
Pre-built workflows that chain the tools:
analyze_ticker(ticker)— full single-stock deep dive (Q-Score + ML + ownership + edges → verdict).find_opportunities(style)— generate and vet a shortlist for a style (value, momentum, growth, hidden gems).market_briefing— top-down snapshot (regime + macro + benchmarks + conviction).
Using the screener
run_screener filters on exact camelCase field names. An unknown field is treated as null server-side and silently excludes every stock, so use the documented names:
trailingPE, priceToBook, pegRatio, marketCap, debtToEquity, currentRatio, grossMargins, operatingMargins, revenueGrowth, earningsGrowth, rsi14, fiftyDayAverageChangePercent, twoHundredDayAverageChangePercent, fiftyTwoWeekHighChangePercent, shortPercentOfFloat, numberOfAnalystOpinions, sector, regularMarketPrice, regularMarketVolume, regularMarketChangePercent.
Margins/growth are decimals (0.25 = 25%); marketCap is raw USD (250000000 = 250M). Operators: gt, gte, lt, lte, eq, between (value: [low, high]), in (value: [string, …]).
The screener reads from StoQuant's cached daily fundamentals (fast, refreshed daily). Prefer run_prebuilt_screen (pre-tuned) or run_screener with universe: "sp500" and a few filters.
Example prompts
"Get the Q-Score for NVDA and explain the top features driving the ML call."
"Show me the top 10 conviction stocks and their current ML outperformance odds."
"What's the current market regime, and which sectors are leading?"
"Run the undervalued-gems prebuilt screen on the sp500 universe."
"Screen sp500 for trailingPE under 15 and debtToEquity under 0.5."
"Get insider activity for PLTR over the last quarter."
Security
Server requires
STOQUANT_API_KEY— fails fast on boot if missing or malformed.All requests use HTTPS. Bearer token in
Authorizationheader. Never logged.Tickers are validated (
^[A-Za-z0-9.\-^]{1,10}$) before any external use.Client-side rate limit: 200 req/min (configurable via
STOQUANT_RATE_LIMIT_RPM).30s per-request timeout (configurable via
STOQUANT_TIMEOUT_MS).Server-side: API key is hashed (SHA-256) at rest, prefix-indexed for fast lookup, timing-safe-compared on verify.
Revoke any key from https://stoquant.com/account/api-keys at any time.
Environment variables
Var | Default | Description |
| — (required) | Your StoQuant API key (free or Power tier) |
|
| API base URL |
|
| Client-side rate limit (req/min) |
|
| Per-request timeout |
|
| Set |
License
MIT
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Maintenance
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