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8 clients · secrets stay placeholders

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{
  "mcpServers": {
    "quant-brain-mcp": {
      "type": "http",
      "url": "https://mcp-quant-brain.onrender.com/mcp"
    }
  }
}

claude mcp add --transport http quant-brain-mcp https://mcp-quant-brain.onrender.com/mcp

[mcp_servers.quant-brain-mcp]
url = "https://mcp-quant-brain.onrender.com/mcp"

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "quant-brain-mcp": {
      "type": "remote",
      "url": "https://mcp-quant-brain.onrender.com/mcp",
      "enabled": true
    }
  }
}

{
  "mcpServers": {
    "quant-brain-mcp": {
      "type": "http",
      "url": "https://mcp-quant-brain.onrender.com/mcp"
    }
  },
  "deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=quant-brain-mcp&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vbWNwLXF1YW50LWJyYWluLm9ucmVuZGVyLmNvbS9tY3AifQ%3D%3D"
}

{
  "servers": {
    "quant-brain-mcp": {
      "type": "http",
      "url": "https://mcp-quant-brain.onrender.com/mcp"
    }
  }
}

{
  "mcpServers": {
    "quant-brain-mcp": {
      "httpUrl": "https://mcp-quant-brain.onrender.com/mcp"
    }
  }
}

extensions:
  "quant-brain-mcp":
    enabled: true
    name: "quant-brain-mcp"
    type: streamable_http
    uri: "https://mcp-quant-brain.onrender.com/mcp"
    timeout: 300

Quality 79 / 100good

protocol75 · weight 25

warn
protocol.modernnewest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
n/a
protocol.statelessonly applies to 2026-07-28 servers
pass
protocol.transportstreamable HTTP
n/a
protocol.list_ttlonly applies to 2026-07-28 servers

authorizationn/a · weight 15

n/a
auth.prm, auth.as_metadata, auth.cimdno remote uses OAuth
n/a
auth.secret_in_urlno templated URL

tool hygiene71 · weight 30

pass
tools.descriptionsevery tool has a description
pass
tools.description_lengthdescriptions are concise
pass
tools.schemasevery tool has an object input schema
fail
tools.annotationsno tool declares readOnlyHint or destructiveHint, so clients cannot tell safe calls from risky ones
fail
tools.directory_hintsno tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: plot_charts (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); scan_watchlist (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); backtest_macd_momentum (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); …
pass
tools.token_costabout 3,948 tokens to load every tool
pass
tools.api_dumptools are not a one-to-one API dump

stability100 · weight 15

pass
stability.changesno tool changes in 30 days
pass
stability.rug_pullno tool changed its meaning under the same name

dependenciesn/a · weight 15

n/a
deps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI package

25 tools, about 3,948 tokens to load them all · tool set 4541e71c8158 · checked 2026-10-20 14:21 UTC

Tool changes

No tool definition changes recorded. A server's first observation is its baseline; later probes record what changes.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.

Trust 64 / 100

unreachable

provenance90

liveness0

freshness85

hygiene100

+repository +namespace-matches-repo +website -unreachable(4 failures) ~updated-65d-ago

Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.

Endpoints

remote	auth	reachable	uptime 30d	p50	protocol	last ok
`https://mcp-quant-brain.onrender.com/mcp` streamable-http	none	no (4 failures)	96%	341 ms	2025-11-25	2026-10-16

Tools (25)

`analyze_momentum`	Momentum indicators: rsi, macd, roc, cci, stoch, stochrsi, tsi, willr. Runs all momentum indicators for the ticker, or only the subset named in `indicators` (e.g. ["rsi", "macd"]). `period` sets the history window: "1d","5d","1mo","3mo","6mo","1y","2y","5y","10y","ytd","max" (default "2y").
`analyze_sector_intelligence_tool`	Analyze sector return, risk, momentum, drawdown and correlation; select best sector.
`analyze_statistics`	Statistical behavior: log_return, zscore, skew, kurtosis, entropy. Runs all statistical indicators for the ticker, or only the subset named in `indicators`. `period` sets the history window: "1d","5d","1mo","3mo", "6mo","1y","2y","5y","10y","ytd","max" (default "2y").
`analyze_technical_levels`	Moving averages and price levels: sma, ema, hma, kama, ichimoku, supertrend, vwap, vwma. Runs all level indicators for the ticker, or only the subset named in `indicators`. `period` sets the history window: "1d","5d","1mo","3mo", "6mo","1y","2y","5y","10y","ytd","max" (default "2y").
`analyze_trend`	Trend strength and direction: adx, aroon, chop, psar, vortex, zigzag. Runs all trend indicators for the ticker, or only the subset named in `indicators`. `period` sets the history window: "1d","5d","1mo","3mo", "6mo","1y","2y","5y","10y","ytd","max" (default "2y").
`analyze_volatility`	Volatility and bands: atr, bbands, donchian, kc, stdev, ui. Runs all volatility indicators for the ticker, or only the subset named in `indicators`. `period` sets the history window: "1d","5d","1mo","3mo", "6mo","1y","2y","5y","10y","ytd","max" (default "2y").
`analyze_volume`	Volume confirmation: obv, cmf, mfi, ad, pvt. Runs all volume indicators for the ticker, or only the subset named in `indicators`. `period` sets the history window: "1d","5d","1mo","3mo", "6mo","1y","2y","5y","10y","ytd","max" (default "2y").
`backtest_macd_momentum`	Run MACD momentum strategy backtest for one ticker. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`backtest_macd_trend_follower`	Run MACD trend follower strategy backtest for one ticker. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`backtest_mean_reversion_rsi_bb`	Run RSI + Bollinger Band mean-reversion strategy backtest. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`backtest_rsi_mean_reversion`	Run RSI mean-reversion strategy backtest. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`backtest_sma_crossover`	Run SMA crossover strategy backtest. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`backtest_trend_crossover`	Run trend crossover strategy backtest. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`backtest_volatility_breakout`	Run volatility breakout strategy backtest. `period`: history window, e.g. "1y","2y","5y","10y" (default "2y").
`build_trade_plan`	Build a sized trade plan: entry, stop, share count, R targets, invalidation. The answer to "what do I do?": given account equity and the percent of it you are willing to risk, returns an entry reference (last close), a structural stop (tighter of recent swing level or 2x ATR, never inside daily noise), the exact number of shares so a stop-out loses only the risk budget, 1R/2R/3R targets, a liquidity check (order as % of 20-day turnover), and a one-line invalidation. Educational analysis, not investment advice.
`find_sector_stock_pipeline_tool`	Run a multi-step pipeline: sector performance -> stock ranking -> strategy selection.
`generate_chart_pack`	Generate the full institutional chart suite for dashboard rendering.
`generate_charts`	Generate charts for portfolio, strategy, quant, fundamentals, and sector pipeline.
`generate_optimized_verdict`	Optimize a portfolio and return backtest metrics plus a final verdict. Args: tickers: List of ticker symbols (e.g. ["AAPL", "RELIANCE.NS"]) amount: Investment amount used for allocation context optimize_type: Optimization mode. Supported values are: "mvo", "hrp", "max_sharpe", "min_volatility", "black_litterman", "cvar", "semivariance". period: History window for price data, e.g. "1y", "2y", "5y", "10y" (default "2y"). Longer windows give the optimizer and backtest more data at the cost of a slower fetch.
`get_company_profile`	Return a full company snapshot with business, valuation, and market metadata.
`get_news`	Recent news headlines for a ticker via Yahoo Finance's news feed. Returns structured articles (title, publisher, url, published_at, summary) for you to read and synthesize. Not a scraper -- uses Yahoo's aggregated feed, so coverage is strongest for large-cap US and Indian names.
`get_quote`	Current price snapshot for one or more tickers (US and Indian). Returns last price, day change %, day and 52-week ranges, position within the 52-week range, and volume vs 3-month average, with an `as_of` timestamp. US quotes are near-real-time; NSE/BSE quotes are ~15 minutes delayed (disclosed in the response). For to-the-second Indian prices during market hours, supplement with a live web search.
`plot_charts`	Alias for chart generation; kept for natural plotting language in clients.
`price_alert`	Persistent price alerts stored server-side (survive restarts, one-shot). Actions: set -- watch a level: price_alert("set", ticker="RELIANCE.NS", level=1270, direction="below", note="stop level") list -- show all active alerts delete -- remove an alert by alert_id check -- fetch current prices for every active alert and return which fired; fired alerts deactivate so they never spam. A server cannot push messages into Claude, so pair this with a scheduled task that calls action='check' on a cadence (e.g. every 30 minutes during market hours) and notifies the user only when 'triggered' is non-empty.
`scan_watchlist`	Scan a watchlist and report which names did something actionable. For each ticker: last close, day change, gap, distance from the 20/50/200-day averages and the 52-week high, ATR%, and volume vs its 20-day average -- plus which rules fired (near_52w_high, volume_spike, crossed_above/below_200dma, at_20dma, gapped_over_1atr). Sorted most-actionable first. The Sunday-evening tool: run it over your list, then feed interesting names into build_trade_plan.

Schemas: list_tools.

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More from io.github.paarths-collab

Official server.json

{
  "name": "io.github.paarths-collab/quant-brain-mcp",
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "remotes": [
    {
      "url": "https://mcp-quant-brain.onrender.com/mcp",
      "type": "streamable-http"
    }
  ],
  "version": "1.0.0",
  "repository": {
    "url": "https://github.com/paarths-collab/quant-brain-mcp",
    "source": "github"
  },
  "websiteUrl": "https://github.com/paarths-collab/quant-brain-mcp",
  "description": "Stock analysis MCP: 38 indicators, 7 optimizers, 8 backtests, US + India sectors."
}