pairbook-mcp

pairbook-mcp

MCP server and CLI for PairBook, the correlation and ETF-overlap engine covering 4,700+ US stocks and ETFs. Any of the 11.3 million possible pairs can be compared: 52,000+ popular pairs come precomputed with issuer-sourced holdings overlap, and every other combination is computed on demand from weekly return series. The underlying JSON API is free and static, needs no key, and refreshes every trading day after the US close.

Ask your AI assistant things like "is my portfolio too concentrated?", "how correlated are QQQ and VOO, and how much do they overlap?" or "find me diversifiers for NVDA" and it can answer with fresh, sourced numbers instead of guessing.

MCP setup

Claude Code

claude mcp add pairbook -- npx -y pairbook-mcp

Cursor: one-click install with

Claude Desktop: add this to claude_desktop_config.json:

{
  "mcpServers": {
    "pairbook": {
      "command": "npx",
      "args": ["-y", "pairbook-mcp"]
    }
  }
}

Any other MCP client works the same way: run npx -y pairbook-mcp over stdio.

Tools

Portfolio analysis

Give it a whole portfolio (2 to 30 positions, weights optional) and it tells you which positions are redundant, where the risk concentrates, what actually diversifies, and whether the ETFs you hold overlap under the hood:

pairbook portfolio AAPL:25 MSFT:25 NVDA:20 JNJ:15 XOM:15

RISK
  volatility     16.7%  (weighted average of the parts: 29.0%)
  beta vs SPY    0.99    market explains 73% of the moves (R2)
  max drawdown   -17.4%  (2024-12-05 to 2025-04-03, SPY: -16.9%)

RISK BUDGET  (share of portfolio risk vs share of capital)
  NVDA   ############  43.1% risk     20% capital  beta 2.18  risk engine  <- 20% of the capital but 43% of the risk
  AAPL   ########      27.1% risk     25% capital  beta 1.06  diversifier
  ...

The MCP tool analyze_portfolio returns the same analysis as structured JSON: Euler risk contributions, diversification ratio and independent risk bets, correlation blocks that move together, drawdown vs SPY, and issuer-sourced overlap warnings between the ETFs held (QQQ and VOO holding 53.5% of the same stocks is something no other portfolio tool reports). Every formula is documented in docs/methodology.md, invariants are covered by tests, and nothing is a forecast or advice.

CLI

The same data in your terminal, no install needed:

npx -y -p pairbook-mcp pairbook QQQ VOO

or after npm i -g pairbook-mcp:

pairbook QQQ VOO         # compare two assets
pairbook NVDA            # one asset's profile
pairbook search nvidia   # find a ticker
pairbook AAPL MSFT --json

Exit codes: 0 on success, 1 on any error (errors go to stderr). --json prints one valid JSON document on stdout, so pairbook qqq voo --json | jq .correlation_weekly just works.

DGRO vs SCHD  (data as of 2026-08-27)
  correlation   1y 0.74   3y 0.88   5y 0.93
  beta vs SPY   DGRO 0.65   SCHD 0.52
  volatility    DGRO 11.4%   SCHD 12.9%
  overlap       20.8% across 32 common holdings (issuer files 2026-08-26)
  https://www.pairbook.io/pair/dgro-vs-schd/

Scope

PairBook is a specialist: correlation, overlap and diversification structure. It pairs well with a general market-data MCP server that brings quotes, fundamentals and news, so install both and let your assistant combine them.

Data

Everything comes from the free PairBook API: correlations computed on weekly returns (1/3/5-year windows), overlap from issuer portfolio disclosures, recomputed every trading day. The dataset is also published as CSV downloads with a DOI.

Free with attribution (a link back to pairbook.io). US-listed stocks and ETFs only. Nothing here is investment advice.

Privacy

The server and CLI run entirely on your machine and are read-only. They call a single host (www.pairbook.io) to fetch public market data, identify themselves with a version and surface string in the user agent, and send nothing else: no prompts, no conversation content, no personal data, no telemetry. Full policy: pairbook.io/privacy.

License

MIT © VoidLab