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@mattral/core

v1.1.0

Published

Shared data model, health scoring, and drift detection algorithms for mcp-reliable

Vulnerabilities

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  • 0High
  • 0Medium
  • 0Low

Links

Git

Maintainers

mattralmattral

Keywords

mcpmodel-context-protocolreliabilityobservabilityhealth-scoredrift-detection

Readme

@mattral/core

Shared data model, health scoring, drift detection, and error classification algorithms for mcp-reliable — pure, dependency-light functions with no Node-specific or MCP-transport code, usable anywhere the same reliability analysis is useful.

npm install @mattral/core

What's in it

  • Health scoring — computeHealthScore(executions): a 0–100 score from success rate, p95 latency, and recency, with documented, independently-derived weightings.
  • Drift detection — detectSchemaDrift, detectOutputShapeDrift, detectLatencyDrift: structural (schema/output-shape) and statistical (latency distribution, via a two-sample Kolmogorov-Smirnov test) detectors for a tool's behavior changing out from under its callers.
  • Error classification — classifyError, summarizeErrorCategories: groups failures into common failure modes (rate-limit, auth, timeout, validation, connection, server-error) from free-text error messages.
  • Alerts & recommendations — driftEventToAlert, detectHealthDegradation, buildRecommendation: turning raw signals into actionable, prioritized guidance.
  • Redaction — redact: strips common PII/secret patterns before anything gets logged or stored.
  • The full Execution, Server, Tool, DriftEvent, Alert, and HealthScore data model, as Zod schemas with inferred types.

Learn more

This package is the algorithmic core of a larger system — see the mcp-reliable GitHub repo for how it fits together, and docs/data-model.md / docs/decisions/ for the reasoning behind each algorithm's specific thresholds and design choices.

License

MIT