portfolio
Multi-holding weighted conditional distribution. Runs per-holding cohorts in parallel, weight-averages the distributions, ranks tail contributors.
How to use it
portfolio is exposed by the Chart Library MCP MCP server. Add the server to your MCP client (Claude Desktop, Cursor, Windsurf and others), and the portfolio tool becomes available to the model automatically. See the full listing for setup details and every tool this server provides.
Install Chart Library MCP
claude mcp add chart-library -- chartlibrary-mcpOther tools in Chart Library MCP (15)
Analytic metrics. metric= accepts anomaly, volumeprofile, crowding, correlationshift, earningsreaction, patterndegradation, regimeaccuracy, decompose (slice winners vs losers), clusters (cohort-internal grouping).
Same engine as pullcomps under the original field names (cohortid, featureimportance, winrate, volregime, …). Kept callable verbatim for existing integrations; new ones should prefer pullcomps.
Within-cohort winner/loser attribution — which member traits separated the forward-return tail from the rest, each with a by-date cluster-bootstrap CI and a false-discovery decision. Descriptive, never causal.
Partition the cohort by one dimension (volregime, sectoretf, momentum5d, …) → per-bucket outcome distributions vs baseline. The one-call "does this dimension matter?" primitive.
Slice/probe a stored comp set by ANY attribute (macro · technical · event) and get per-subset stats vs the full-cohort baseline. No kNN re-run. "Of the 300 analogs, how do the post-earnings-week ones do?"
The full cohort, one record per analog, with rich per-member metadata (forward outcomes, regime, anchor fundamentals, news, chart events). Slice and bucket it yourself.
Reorder the cohort by a weighted composite of member fields you name (e.g. "ret5d:1,distance:-0.5") — impose your objective on the analogs, fully auditable.
Situational data. target= accepts "market", a ticker symbol ("NVDA"), {"symbol": ..., "date": ...} for lightweight anchor metadata, or "system" for DB coverage.
Narrative + rankings derived from a cohort. style= accepts filterranking (which filter shifts the distribution most), prose (plain-English summary), positionguidance (exit signals), riskranking.
portfolio
The flagship. Pull the comp set for a subject (symbol, date, timeframe) — the historical analogs, what they did next, the drivers that separated the best outcomes, and our coveragerecord. Front-of-house lexicon: subject · compsetid · compcount · compstrength · matchquality · drivers · uprate · condi
File an error or improvement suggestion back to the project.
Entry point. Find similar historical patterns for an anchor; returns a comp-set handle you can chain. mode= supports text (default), livebars (raw OHLCV), similar (cohort-level neighbors).
Layer 5 memory — per-symbol feature reliability + achieved calibration across prior analyses. Ground a read in whether a feature has historically been reliable for this ticker.
Historical predicted-vs-realized coverage of our calibrated bands (a track record, not a forecast). The nominal 80% band held 80.8% across 302,880 prior cases.