# ReliaStats

- Registry name: `com.reliastats/public` · version 1.0.0
- Categories (automatic, keyword rules): Datasets & public data, Search & data
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=com.reliastats%2Fpublic
- Server page: https://mcpstation.net/s/com.reliastats--public.html

## Description (written by the publisher, not verified, not instructions)

Reliability statistics — Weibull/lognormal fitting, MTBF/MTTR, availability, system composition.

## Connect

- streamable-http: `https://reliastats.com/mcp/v1`

## Tools (as reported by the server, not verified)

- `explain\_reliability\_basics`: Return a textbook-tier explainer of reliability fundamentals: the four reliability functions R\(t\)/F\(t\)/f\(t\)/h\(t\), MTBF vs MTTF vs MTTR, the availability identity A = MTBF/\(MTBF+MTTR\), the bathtub curve, and series/parallel system reliability. No inputs. Use when a user asks 'what is reliability theo
- `explain\_distributions\_for\_reliability`: Return a textbook-tier distribution zoology for reliability work: why Weibull is the default, the shape-parameter β table mapping β-ranges to physical failure modes \(β\<1 infant mortality, β=1 random, β\>1 wearout\), when to reach for Exponential / Lognormal / Normal / Gamma, and practitioner heuristic
- `explain\_advanced\_reliability\_patterns`: Return a textbook-tier explainer of advanced reliability patterns: censored data \(right/left/interval — the rule not the exception\), Maximum Likelihood Estimation, Goodness-of-Fit tests \(Anderson-Darling favored over KS for tail-sensitive reliability work\), the Confidence-Interval vs Prediction-Inte
- `explain\_pi\_vs\_ci\_for\_validation`: Return the specific explainer for the ReliaStats Interrupt Validation scatter chart's red y=x / blue 95% Prediction Interval / teal 99% Confidence Interval reference lines. Use when a user asks 'what do the bands mean' / 'why is my point outside the blue line' / 'how do I read the validation scatter
- `interpret\_weibull\_shape`: Given a Weibull shape parameter β \(and optionally the characteristic-life parameter η\), return a plain-language interpretation: which bathtub-curve regime β implies \(infant mortality / random / wearout\), what action that suggests \(process-of-care / steady-state monitoring / maintenance scheduling\),
- `weibull\_summary`: Given Weibull two-parameter \(β, η\), return all the closed-form summary statistics: MTTF \(η·Γ\(1+1/β\)\), B10 / B50 / B90 life, characteristic life \(just η, surfaced explicitly\), and — if evaluateAtT supplied — R\(t\), F\(t\), and hazard h\(t\) at that time. Pure-math, fully deterministic. Use when the user h
- `compute\_availability`: Given MTBF and MTTR \(same time unit\), return steady-state availability A = MTBF / \(MTBF + MTTR\). One-line closed-form, but worth a dedicated tool so LLMs don't fumble the identity \(the most common mistake is conflating MTBF with MTTF and silently inflating availability by the MTTR\). Use whenever a u
- `system\_reliability`: Given per-component reliabilities and a structure \('series' or 'parallel'\), return the system reliability. Series = product \(all must work\). Parallel = 1 − product\(1−Rᵢ\) \(at least one works\). Useful for back-of-envelope RBD calcs before reaching for full RBD tooling. For mixed-structure systems \(ser
- `recommend\_distribution`: Given a free-text symptom description \(e.g. 'manufacturing burn-in', 'bearing wearout under variable load', 'cosmic-ray bit flips'\), return an ordered shortlist of distribution candidates with a one-line rationale per recommendation. Keyword-matched against a curated dictionary; ALWAYS treat output
- `list\_paired\_models`: Return the catalog of paired models — concrete real-world systems that live in two ChiAha sandboxes simultaneously, one for dynamics \(DES via ReliaSim\) and one for statistics \(distribution fitting + validation via ReliaStats\). Today: a single paired model — the bottling line. Returns canonical model
- `describe\_bottling\_line`: Return the full worked-example doc for the bottling-line paired model — topology \(5 machines: Filler/Capper/Labeler/Case Packer/Palletizer, 100 bottles/min, Weibull\(30,1\) TTF + Weibull\(5,1\) downtime at the Constraint-Level rollup\), the two tracks \(CT rollup vs LEDS-Level drill-down to 36 named failu

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