Fmeca

io.github.praxecPublished by GitHub account praxecv0.2.2Updated Oct 30, 2026

Deterministic, offline FMECA MCP server: failure modes, criticality matrix, mitigations, readiness

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Overview

AI-generated overview

Offline, deterministic FMECA engine that lets an assistant record failure modes and mitigations and get computed criticality, residual risk and sign-off…

What you can do
  • Open, resume and list analysis sessions with fixed metadata and a chosen matrix strategy
  • Add failure modes, mitigations and re-scores, set mitigation status and dispositions, and get recomputed state
  • Read the current state, the next highest-risk item, and the readiness gate
  • Export the full FMECA table and list the fixed observation vocabulary per strategy
  • Run a stateless one-shot analysis, or suggest actions and list risk policies read-only
When to use it
Useful when an assistant should help run a structured risk triage — enumerating failure modes, ranking criticality and tracking mitigations — with scores derived by code rather than proposed by the model, and with results kept as logs in a project repository.
Requirements
Runs locally over stdio; install via the npm launcher, a prebuilt binary, or the container image, or build from source with Cargo. State lives in a .fmeca/ folder or the directory set by FMECA_STATE_DIR. The optional vet tool needs OPENROUTER_API_KEY in the environment; FMECA_JEV_MODEL and FMECA_JEV_TIMEOUT_SECS tune it.
Before you install
The vet tool sends analysis content to OpenRouter using OPENROUTER_API_KEY, so treat that key as a secret and expect data to leave the machine. Session tools append to an event log and change analysis state; failure modes are never deleted, only excluded with evidence. The README's Docker example passes OPENROUTER_API_KEY into the container.

Installation

In SourceWeft

  1. Open Fmeca in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

fmeca-mcp

[CI] [crates.io] [docs.rs] [License: Apache-2.0]

fmeca-mcp is a structured FMECA engine exposed as an MCP server. You feed it failure modes and the observations that characterise them; it derives the severity/probability scores, computes criticality off a fixed matrix, tracks mitigations under a prevent→detect→fail-fast discipline, and tells you whether the analysis is ready to sign off. Any MCP client (Claude Code, Cursor, or a custom orchestrator) drives it over the standard protocol.

For AI agents: to install the server and its skills for your client, follow docs/AGENT-INSTALL.md.

What is FMECA

Failure Modes, Effects & Criticality Analysis is a structured risk-triage method: enumerate how a thing can fail, judge how bad each failure is (severity) and how likely it is (probability), and rank the combined criticality so the worst risks get addressed first. Mitigations are then layered on and the residual risk is re-assessed. fmeca-mcp owns the structure and the arithmetic of that process; the caller supplies the domain judgement.

Design principle: deterministic, offline, no LLM-supplied numbers

The engine is a pure function of (events in) → (criticality + residual + gaps + readiness out). It does no I/O beyond an append-only event log, makes no network calls, and runs no model.

Crucially, the caller never supplies a score. A caller (often an LLM) does the fuzzy work — naming a failure mode, its cause and effect, and proposing mitigations — and supplies observations drawn from a fixed catalog (e.g. data_loss, happens_in_normal_use). The kernel maps those observations to severity/probability levels through a locked evidence→score map and reads criticality off a fixed, locked S×P matrix. The model proposes; the code scores. Because criticality, residual risk, standing, and readiness are computed by a fold over the event log — never stored, never accepted as input — the same analysis always yields the same result, and no model can talk the matrix into a softer answer.

Install

npx (no install step)

sh
npx -y @matthew-cochran/fmeca

The npm launcher downloads the matching release binary, verifies its checksum, caches it and runs it. The package installs two command aliases, fmeca and fmeca-mcp, both running the same launcher. Point your MCP client at either command (see MCP client config).

Prebuilt binary (no Rust, Cargo, or Git required)

sh
# Linux / macOScurl -fsSL https://github.com/praxec/fmeca/releases/latest/download/install.sh | sh
# Windows (PowerShell)irm https://github.com/praxec/fmeca/releases/latest/download/install.ps1 | iex

The installer resolves your OS and CPU architecture, downloads the matching release asset, verifies its SHA-256 against the release's checksums.sha256, extracts it safely, and atomically installs the binary into a user-local managed directory ($HOME/.local/bin on Linux/macOS, %LOCALAPPDATA%\Programs\fmeca-mcp on Windows). It never compiles from source and fails loudly on an unsupported OS/architecture.

Pin a specific release instead of the current latest stable:

sh
curl -fsSL https://github.com/praxec/fmeca/releases/latest/download/install.sh \  | sh -s -- --version v0.1.0

The installers can also be fetched from a specific release, for example https://github.com/praxec/fmeca/releases/download/v0.1.0/install.sh.

The installer scripts are published as release assets alongside the binaries.

Or download the archive directly. Every release publishes a checksums.sha256 and a machine-readable release-manifest.json listing each target, asset, digest, version, and source SHA:

OSArchTarget tripleAssetBuild supportRuntime smoke tested
Linuxx86_64x86_64-unknown-linux-gnufmeca-mcp-x86_64-unknown-linux-gnu.tar.gznative CInative CI
Linuxarm64aarch64-unknown-linux-gnufmeca-mcp-aarch64-unknown-linux-gnu.tar.gznative CInative CI
macOSx86_64x86_64-apple-darwinfmeca-mcp-x86_64-apple-darwin.tar.gznative CInative CI
macOSApple Siliconaarch64-apple-darwinfmeca-mcp-aarch64-apple-darwin.tar.gznative CInative CI
Windowsx86_64x86_64-pc-windows-msvcfmeca-mcp-x86_64-pc-windows-msvc.zipnative CInative CI
Windowsarm64aarch64-pc-windows-msvcfmeca-mcp-aarch64-pc-windows-msvc.zipnative CInative CI

"Native CI" means each asset is built and its MCP initialize/tools/list handshake smoke-tested on that platform's own runner. No other CPU/OS combination is claimed; unsupported platforms are rejected rather than silently cross-compiled.

Updates

Re-run the installer to update. Only the binary in the managed install directory is replaced (atomically); application state and configuration live outside that directory and are never overwritten. See Configuration for where state goes.

Docker

sh
docker run -i --rm ghcr.io/praxec/fmeca:0.1.0

Mount your project to keep analyses in its .fmeca/ folder (without a mount the state is lost when the container exits). FMECA_STATE_DIR points the server at that folder even before fmeca-mcp init has created it:

sh
docker run -i --rm --user "$(id -u):$(id -g)" -v "$PWD:/work" -w /work -e FMECA_STATE_DIR=/work/.fmeca -e OPENROUTER_API_KEY ghcr.io/praxec/fmeca:0.1.0

From source

sh
cargo install fmeca-mcp

cargo install works once the crate is published to crates.io. Until then, build from a checkout with cargo build --release.

MCP client config

It speaks MCP over stdio (the standard transport). Wire it into your editor like any other MCP server. The same entry works in Claude Code (.mcp.json) and Copilot (.mcp.json) (Cursor needs "type": "stdio"; see its section in AGENT-INSTALL):

json
{  "mcpServers": {    "fmeca": {      "command": "npx",      "args": ["-y", "@matthew-cochran/fmeca"]    }  }}

Use "command": "fmeca-mcp" (or its alias "command": "fmeca") with "args": [] for the binary. Codex uses TOML:

toml
[mcp_servers.fmeca]command = "npx"args = ["-y", "@matthew-cochran/fmeca"]env_vars = ["OPENROUTER_API_KEY"]

Every client, with the skills install for each (including Cursor's .cursor/mcp.json entry), is in docs/AGENT-INSTALL.md. The key is optional (only vet uses it) and is never written to a config file: pass it as "env": { "OPENROUTER_API_KEY": "${OPENROUTER_API_KEY}" } where the client expands variables, or let the server inherit it from the environment.

Tool surface

ToolDoes
session.openStart or resume a session; optionally selects the matrix strategy and records analysis metadata (title, level, aspect, scope_paths, parent), all fixed for the session's life.
appendAdd a failure mode (add_failure_mode), add a mitigation (add_mitigation), or re-score an existing failure mode (rescore). set_mitigation_status moves a mitigation through planned, implemented, verified or abandoned (verified needs evidence other than a note). set_failure_mode_disposition accepts a failure mode's residual risk (needs an approver) or excludes it as not credible (needs evidence); failure modes are never deleted. Returns the recomputed state.
state.getRead-only projection of the session: every failure mode with its computed criticality, residual, and standing.
risk.nextThe highest-criticality unmitigated failure mode — what to address next.
readiness.assessThe readiness gate: is every High/Medium residual reduced and every blocker cleared?
report.exportThe full FMECA table for the session.
scoring.catalogThe fixed observation vocabulary for a strategy — the ids the caller draws from.
analyzeStateless one-shot: hand over an entire analysis, get back the entire computed report. No session, no persistence.
session.listEvery analysis in the state dir (the project's .fmeca/ when there is one), with its metadata, standing counts (excluded failure modes are counted separately), ready, ready_verified and resolution counts. Filters: level, aspect, parent. A log that fails to replay is listed with its error.
vetAdvisory: asks Jev (via OpenRouter, needs OPENROUTER_API_KEY) whether observations, mitigations, coverage and readiness hold up, and returns probabilities beside the deterministic gate. Never writes or changes a score; without a key it reports vet_unavailable.
actions.suggestRead-only. Reads a session (or an inline analysis) under a risk policy and suggests actions: per-failure-mode risk bands, evidence confidence, dispositions, tagged actions and a sign-off verdict. Never changes the analysis or the log.
policy.listRead-only. The built-in policy presets and the project's .fmeca/policies/ files, each with its name, hash and class. A project file that does not load is listed with its error.

The analyze tool reuses the exact same kernel compute as the session path, so the two can never diverge.

Keep analyses in your repo (.fmeca/)

sh
fmeca-mcp init                 # at the project root: creates .fmeca/git add .fmeca && git commit -m "chore: add .fmeca"fmeca-mcp check --dir .fmeca   # in CI: replays every log, catches duplicate ids

Launch the server from the project root (or set FMECA_STATE_DIR) and it keeps one log per analysis in .fmeca/, named <aspect>-<level>. The setup, merge behaviour, Docker mount and the skill for each level are in docs/AGENT-INSTALL.md.

Risk policies

A risk policy reads an analysis through your project's own risk bands, sets a sign-off rule, and suggests tagged actions (design, review, test, ops, process, docs, security). It is computed when you ask and is never written to the log, so one analysis can be read under several policies. fmeca suggests; it never acts.

Presets: compat-0.1 (the default; its sign-off equals readiness.assess), prototype, standard, business-critical, safety-critical and confidence-view. Your own policies are TOML files in .fmeca/policies/<name>.toml and resolve after the presets.

sh
fmeca-mcp policy list                                   # presets and project filesfmeca-mcp policy validate .fmeca/policies/team.toml     # ok <name> <hash>, or the errorfmeca-mcp suggest checkout-implementation --policy standard --format markdown

suggest exits 0 when the policy's sign-off passes, 1 when it fails (usable in CI) and 2 on a usage or policy error. Agents call the same thing as the actions.suggest and policy.list tools. The model, every preset and the action catalog are in docs/policies.md.

Configuration

VariableDefaultEffect
FMECA_STATE_DIRnearest .fmeca/, else $XDG_DATA_HOME/fmeca-mcp (or $HOME/.local/share/fmeca-mcp), else ./fmeca-stateWhere the per-session logs live.
OPENROUTER_API_KEYunsetEnables the optional vet tool. Read from the environment only.
FMECA_JEV_MODELtypesafe/jev-1.13The model vet asks.
FMECA_JEV_TIMEOUT_SECS30vet request timeout, in seconds.

Matrix strategies

The criticality matrix is a closed, code-resident strategy selected at session.open (and fixed for the session's life). Each strategy ships with a locked S×P matrix and its own scoring catalog:

StrategyScaleNotes
qualitative3x3Low / Medium / HighThe default 3×3 qualitative matrix.
nasa8004_5x55×5 consequence × likelihoodThe NASA GSFC-HDBK-8004 risk matrix.

The caller selects a strategy; it never edits a strategy's cells.

Use fmeca as a library

The kernel is a plain Rust library, independent of MCP. The stateless analyze function takes a strategy and a batch of failure modes and returns the full computed report:

rust
use fmeca::{    analyze, AnalyzeInput, AnalyzeMitigation, Domain, EntityRef, MatrixStrategy, MitigationKind,};
let failure_modes = vec![AnalyzeInput {    id: "fm-1".into(),    component: EntityRef::new("checkout-service"),    description: "Payment double-charge on retry".into(),    cause: Some("Non-idempotent charge endpoint".into()),    effect: Some("Customer billed twice".into()),    domain: Domain::Runtime,    scope: None,    // Observations, not scores — the kernel derives severity/probability.    severity_observations: vec!["data_loss".into()],    probability_observations: vec!["happens_in_normal_use".into()],    mitigations: vec![AnalyzeMitigation {        id: "m-1".into(),        kind: MitigationKind::Prevention,        description: "Idempotency key on the charge endpoint".into(),        residual_severity_observations: vec![],        residual_probability_observations: vec!["rare_edge_case".into()],    }],}];
let report = analyze(MatrixStrategy::default(), &failure_modes).unwrap();println!("risk ranking: {:?}", report.risk_ranking);println!("ready: {} blockers: {:?}", report.ready, report.blockers);// report.failure_modes carries per-FM criticality / residual_criticality /// standing / response_class / issues.

For long-lived, multi-turn analyses use fmeca::Engine over a StateStore (a FilesystemStore is provided), which persists an append-only event log and replays it to compute state. See the API docs.

Development

sh
cargo buildcargo testcargo fmt --allcargo clippy --all-targets -- -D warnings

The agent skills under skills/ are embedded in the binary at build time. After adding or removing a skill, a local incremental build does not notice; run touch crates/fmeca-mcp/build.rs and build again.

CI runs build + test on Linux/macOS/Windows, plus rustfmt and clippy (warnings are denied). Please make sure those pass locally before opening a pull request.

Using it with Praxec

This is an MCP tool used by Praxec packs. The easiest way to get it — and a workflow pack that uses it — up and running is the one-command setup:

bash
curl -fsSL https://raw.githubusercontent.com/praxec/packs/main/setup.sh | bash

See the pack registry for this tool's provider coordinates (container image / release binary) and which packs depend on it.

License

Apache-2.0.

Source: README.md at commit 9f501e3

Tools

0
SourceWeft started this package once in an isolated sandbox, without credentials, to list its tools. That failed: the package type cannot run in the sandbox.

Version history

3
  1. v0.2.2LatestOct 22, 2026
  2. v0.2.1Oct 20, 2026
  3. v0.2.0Oct 12, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts