ReliaStats

Connect it to your AI

Claude Code

claude mcp add --transport http public https://reliastats.com/mcp/v1

Claude, ChatGPT, Cursor and other apps

Add it as a custom connector with this URL (Streamable HTTP):

https://reliastats.com/mcp/v1

Cursor, VS Code and other apps (mcp.json)

{
  "mcpServers": {
    "public": {
      "url": "https://reliastats.com/mcp/v1"
    }
  }
}

Tools it offers

11 tools, as the server itself reported during our check on Oct 31, 2026.

• explain_reliability_basicsReturn 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/parall
• explain_distributions_for_reliabilityReturn 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 t
• explain_advanced_reliability_patternsReturn 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
• explain_pi_vs_ci_for_validationReturn 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' /
• interpret_weibull_shapeGiven 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
• weibull_summaryGiven 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), a
• compute_availabilityGiven 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 M
• system_reliabilityGiven 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
• recommend_distributionGiven 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 re
• list_paired_modelsReturn 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 ReliaS
• describe_bottling_lineReturn 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-Lev

Questions