Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Deterministic, offline FMECA MCP server: failure modes, criticality matrix, mitigations, readiness
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"fmeca": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/fmeca:0.2.2"
]
}
}
}ターミナルでこれを実行します
claude mcp add fmeca -- docker run -i --rm ghcr.io/praxec/fmeca:0.2.2プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"fmeca": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/fmeca:0.2.2"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"fmeca": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/fmeca:0.2.2"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント praxec で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.2.2)がレジストリに届いたのは15 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにDockerも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, TF Rooms
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Live room availability, rates and stay quotes for 12 New Leaf motels in Twin Falls, Idaho.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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.
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.
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.
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).
# Linux / macOS
curl -fsSL https://github.com/praxec/fmeca/releases/latest/download/install.sh | sh
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:
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:
| OS | Arch | Target triple | Asset | Build support | Runtime smoke tested |
|---|---|---|---|---|---|
| Linux | x86_64 | x86_64-unknown-linux-gnu | fmeca-mcp-x86_64-unknown-linux-gnu.tar.gz | native CI | native CI |
| Linux | arm64 | aarch64-unknown-linux-gnu | fmeca-mcp-aarch64-unknown-linux-gnu.tar.gz | native CI | native CI |
| macOS | x86_64 | x86_64-apple-darwin | fmeca-mcp-x86_64-apple-darwin.tar.gz | native CI | native CI |
| macOS | Apple Silicon | aarch64-apple-darwin | fmeca-mcp-aarch64-apple-darwin.tar.gz | native CI | native CI |
| Windows | x86_64 | x86_64-pc-windows-msvc | fmeca-mcp-x86_64-pc-windows-msvc.zip | native CI | native CI |
| Windows | arm64 | aarch64-pc-windows-msvc | fmeca-mcp-aarch64-pc-windows-msvc.zip | native CI | native 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.
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 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:
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
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.
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):
{
"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:
[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 | Does |
|---|---|
session.open | Start 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. |
append | Add 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.get | Read-only projection of the session: every failure mode with its computed criticality, residual, and standing. |
risk.next | The highest-criticality unmitigated failure mode — what to address next. |
readiness.assess | The readiness gate: is every High/Medium residual reduced and every blocker cleared? |
report.export | The full FMECA table for the session. |
scoring.catalog | The fixed observation vocabulary for a strategy — the ids the caller draws from. |
analyze | Stateless one-shot: hand over an entire analysis, get back the entire computed report. No session, no persistence. |
session.list | Every 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. |
vet | Advisory: 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.suggest | Read-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.list | Read-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.
.fmeca/)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 - . The setup, merge behaviour, Docker mount and the skill for each level are in docs/AGENT-INSTALL.md.
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/ .toml and resolve after the presets.
fmeca-mcp policy list # presets and project files
fmeca-mcp policy validate .fmeca/policies/team.toml # ok , or the error fmeca-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.
| Variable | Default | Effect |
|---|---|---|
FMECA_STATE_DIR | nearest .fmeca/, else $XDG_DATA_HOME/fmeca-mcp (or $HOME/.local/share/fmeca-mcp), else ./fmeca-state | Where the per-session logs live. |
OPENROUTER_API_KEY | unset | Enables the optional vet tool. Read from the environment only. |
FMECA_JEV_MODEL | typesafe/jev-1.13 | The model vet asks. |
FMECA_JEV_TIMEOUT_SECS | 30 | vet request timeout, in seconds. |
The criticality matrix is a closed, code-resident strategy selected at session.open (and fixed for the session'
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