
Fmeca
io.github.praxec由 GitHub 帳號 praxec 發布v0.2.2更新於 Oct 30, 2026
Deterministic, offline FMECA MCP server: failure modes, criticality matrix, mitigations, readiness
概覽
離線、確定性的 FMECA 引擎,讓助理記錄失效模式與緩解措施,並取得計算出的嚴重度、剩餘風險與簽核就緒度。
- 可以做什麼
- 開啟、接續並列出分析工作階段,固定中繼資料與所選矩陣策略
- 新增失效模式、緩解措施與重新評分,設定緩解狀態與處置,並回傳重算後的狀態
- 讀取目前狀態、下一個最高風險項目以及就緒度關卡
- 匯出完整 FMECA 表格,並列出各策略固定的觀測詞彙
- 執行無狀態的一次性分析,或以唯讀方式提出行動建議並列出風險策略
- 適用情境
- 適合讓助理協助進行結構化風險分級:列舉失效模式、排序關鍵度並追蹤緩解措施,分數由程式碼推導而非模型提出,結果以日誌形式保存在專案儲存庫中。
- 執行需求
- 以 stdio 在本機執行;可透過 npm 啟動器、預先建置的執行檔或容器映像安裝,也可用 Cargo 從原始碼建置。狀態保存在 .fmeca/ 資料夾或 FMECA_STATE_DIR 指定的資料夾。選用的 vet 工具需要環境變數 OPENROUTER_API_KEY,FMECA_JEV_MODEL 與 FMECA_JEV_TIMEOUT_SECS 用於調整。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Fmeca,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
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)
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)
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:
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:
"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
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:
From source
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):
Use "command": "fmeca-mcp" (or its alias "command": "fmeca") with
"args": [] for the binary. Codex uses TOML:
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
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/)
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.
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
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:
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:
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
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:
See the pack registry for this tool's provider coordinates (container image / release binary) and which packs depend on it.
License
來源:README.md,提交 9f501e3
工具
0版本歷史
3- v0.2.2最新Oct 22, 2026
- v0.2.1Oct 20, 2026
- v0.2.0Oct 12, 2026
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