Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Code changes and unit tests by local MLX models, behind a gate a machine can run.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"sidecrew": {
"command": "npx",
"args": [
"-y",
"sidecrew",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add sidecrew -- npx -y sidecrew mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"sidecrew": {
"command": "npx",
"args": [
"-y",
"sidecrew",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"sidecrew": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"sidecrew",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 lvlrSajjad 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.0)은 43일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, topo^alpin
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Avalanche bulletins and mountain weather forecasts for any place in the Alps.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
You ask for a change to your source code, and you get it — made on your Mac, by models that cost you no Claude tokens, and only after a machine has checked it.
Claude Opus plans the work and reviews what came back. Small models running locally (MLX, no network) do the narrow parts. Between them sits a gate a machine can run — for a code change: the diff stayed where it was asked to, tsc is clean, and every test that passed before still passes. Claude never sees anything that did not survive it.
$ sidecrew fix change_plan.json
fix 2026-09-20T09-14-02Z-rename: 1 step, 12 tasks, 13.0 GB free ÷ 6.5 GB per slot = 2; 1 worker up step 1/1 "rename the helper": capturing the baseline rename-01: survived (src/util/asset.util.ts) rename-02: survived (src/util/asset.util.ts, src/util/asset.util.spec.ts) … multi-06: failed at compile · escalating — renamed the symbol 7 times over, 5 compile errors 11/12 survived · 0 → 0 tsc errors · .sidecrew/runs/2026-09-20T09-14-02Z-rename/result.json
*Illustrative shape, not a captured transcript* — it is the real output format with the counts from the React measurement below, and no client's file names. 11 of 12 with a 95 % interval of `[0.615, 0.998]` is the number; the line above is what it looks like while it runs.
Unit tests are workload #1 — the same shape with a mutation-kill gate instead — and the numbers for both are below, each with its interval.
sidecrew needs 24 GB of installed RAM. Below that a 7B cannot sit beside a normal working set (measured), so sidecrew refuses to run and tells you why rather than quietly becoming a different tool (ADR-0073). sidecrew doctor answers this before you plan anything.
And the other half of the ledger, measured 19–20 Sep 2026: the workers are free, the *coordination* is not. Opus planning costs 8,400–22,100 tokens per task, depending almost entirely on how many tasks are in the plan — see *What this costs to run* below. A page that says "the work is free" without saying that is telling you half of it.
Every rate on this page is an interval, never a point, and the reason is measured. Replaying a frontier model's own diffs — which the gate finds no defect in — through the gate a second time, it disagreed with itself on 2 of 19 candidates: D = 0.105, 95 % interval [0.013, 0.331] (experiments/gate-error-rate/, against a rule frozen before the first replay). That rule's own verdict at D > 0.10 is UNACCEPTABLE, and its consequence is this paragraph: no survival rate here is published as a bare fraction, D travels beside each of them, and no two of our rates are compared without asking whether their difference survives it.
What that does and does not damage. D counts the gate refusing changes that were fine. Nothing in it is evidence of the gate *admitting* something bad. So:
*The gate admits nothing that fails* — stands.
*The gate refuses only things that fail* — **measured false, at roughly one evaluation in ten, and
unproven at any tighter bound.**
Two of the three known causes are now recorded on every verdict — memory pressure (ADR-0066) and a baseline captured on a different calendar day (ADR-0069). The third is undiagnosed, and both measured disagreements happened on a quiet machine, so it is neither of the first two. D was measured on workload #2a's gate; it says nothing about workload #1's mutation gate, which is a different oracle (§4.4 of the rule).
Against a decision rule frozen before the tool had produced a single verdict (experiments/go-no-go-2a/results/REPORT.md). S is survival, A is a blind reviewer's approval of the diff. Every cell is k/n with its exact 95 % interval; D = 0.105 [0.013, 0.331] applies to every S.
| input | S, local 7B | S, Haiku control | A, local 7B | A, control |
|---|---|---|---|---|
| fixture | 3/3 [0.292, 1.000] | 3/3 [0.292, 1.000] | 1/3 `[0.008, 0.906]` | 3/3 [0.292, 1.000] |
| a commercial Nest/jest codebase | 12/12 [0.735, 1.000] | 12/12 [0.735, 1.000] | 9/10 [0.555, 0.997] | 10/10 [0.692, 1.000] |
| a commercial React/jest codebase | 11/12 [0.615, 0.998] | 12/12 [0.735, 1.000] | 9/10 [0.555, 0.997] | 10/10 [0.692, 1.000] |
Read the intervals, not the fractions: at these sample sizes 12/12 and 11/12 are not distinguishable, and neither is the 7B from the control on A. Both real projects passed the frozen rule by a margin of exactly zero, on a sample of ten. The survival rate decided nothing — five of six measurable cells sit at or above 0.917, so the rule's ratio clauses were inert, and the only thing that separated a local 7B from a network model was the approval rate.
What that approval rate is about, measured: the local model makes unrequested cosmetic edits — a deleted docblock, a reworded comment, a stray blank line — in 4 of 23 `[0.050, 0.388]` sampled survivors, against the control's 0 of 23 `[0.000, 0.148]`. confined ∧ compiles ∧ tests pass cannot see any of it, which is the point.
Measured 18–19 Sep 2026 against the thing a colleague actually does today — asking a frontier model directly, one task at a time, with no plan and no gate. Same 19 hand-written tasks, same two codebases, four arms.
| Opus alone | Sonnet alone | sidecrew | |
|---|---|---|---|
| tokens, 19 tasks, Nest codebase | 80,131 | 88,820 | 0 |
| tokens, 19 tasks, React codebase | 95,335 | 88,680 | 0 |
| output vs Opus, Nest codebase | — | identical 19/19 | identical on 18 of 19 |
| changes delivered and verified, Nest | 19 (unverified) | 19 (unverified) | 19/19 `[0.824, 1.000]` survived |
| changes delivered and verified, React | 19 (unverified) | 19 (unverified) | 15/19 `[0.544, 0.939]` survived; 4 escalated |
The token columns are counts and are exact. The survival rows are rates, so they carry their intervals, and D = 0.105 [0.013, 0.331] applies to both of them.
A fourth arm ran the same gate over Opus's own diffs, to separate the gate's contribution from the worker's: 19/19 `[0.824, 1.000]` on the Nest codebase and 18/19 `[0.740, 0.999]` on the React one. Two things follow, and the second is the more useful.
The gate found nothing wrong with a frontier model's work. Its single rejection there is a tsc fragility it rejects from *both* arms — so on these tasks the gate adds no safety on top of Opus. Its entire value is that it makes the free worker usable, not that it second-guesses the expensive one.
And it is what separates a worker defect from a project defect. Of the four React failures, three vanish when Opus writes the diff — genuine worker defects — and one reproduces exactly, because the 7B's output for that task was *byte-identical* to Opus's. Worker-attributable survival is therefore 15/18 `[0.586, 0.964]`, not 15/19. Without that control the small model would have been blamed for a third more failures than it caused — and note that the two intervals overlap almost entirely, so the correction changes the *attribution* rather than the number.
Three things that buys you, and one it costs.
escalated, each with the exact errors, none merged. Asking Opus directly gives you a diff and the sentence *"nothing else changed"* — accurate here, and unverified.tsc). It is free and unattended, not fast.What is not claimed. The frozen rule's verdict is WITHHELD: every task in these runs is a rename, and the rule refuses a verdict until at least half are null guards, API migrations or dead-code removal. The measurement vindicated that clause rather than surviving it — two frontier models and a 7B emitted *identical bytes* on 18 of 19 Nest tasks, so that task set cannot rank anything. experiments/status-quo/ has the arms, the protocol frozen before they ran, and the defects.
| OS | macOS on Apple silicon. The local worker is MLX, which is Apple's. Not a port away — a different inference stack. |
| RAM | 24 GB installed or more for the local tier and everything this page measures. The threshold is on *installed* RAM, never free, so a machine that can host a worker never falls back silently. |
| Node | ≥ 20. A project whose own engines demands newer is honoured — run sidecrew under the project's Node (ADR-0049 cost a night to learn). |
| Python | mlx-lm, installed by you: pip install mlx-lm. Deliberately not bundled — external capabilities are shelled out and reported by doctor, never vendored. |
| Disk | ~4 GB for the 7B (downloaded on first sidecrew serve, pinned revision), plus ~500 MB per verification sandbox while a run is in flight. |
| The project | TypeScript with a green-ish tsc and a test suite that runs. Workload #1 also does Swift/XCTest. |
Under 24 GB: sidecrew still runs, on the api tier, with Haiku as the worker billed to your key — and none of the numbers on this page describe that tier, because they have not been measured (Phase 13 §5). Supported, and unpriced. If that matters to you, 24 GB is the line.
Windows and Linux: no. The TypeScript verifier would port, but the worker would not, and memory and pressure detection are sysctl/vm_stat. sidecrew doctor tells you rather than failing oddly.
The check is on installed RAM, never free RAM — free RAM swings by 8 GB when you open Xcode, and a tool that changes what it is based on that is a tool you cannot reason about. The floor is 24 GB and below it sidecrew refuses (ADR-0073).
| installed | tier | worker | gates in flight | what that means for you |
|---|---|---|---|---|
| under 24 GB | — | none: sidecrew refuses | — | A 7B cannot sit beside a normal working set here (measured), and trying anyway means swapping — which makes the gate reject changes that were fine (ADR-0066). You are told your RAM, the floor and the reason. There is an unsupported escape hatch (SIDECREW_TIER=api, Haiku over the network, billed to your key, never measured); it is not what any number on this page describes. |
| 24–32 GB | local | 7B on your Mac | 1 | Everything on this page was measured here. Worker tokens are zero. One task at a time: ~4 min each, so a 19-task plan is ~70 min, unattended. Memory is the binding constraint — see the false-negative note below. |
| 48–64 GB | local | 7B, or a 14B comfortably | ~3 *(estimated)* | The gate stops competing with the model for memory. The same 19-task plan should land nearer ~25 min *(estimated)*, and ADR-0066's whole false-negative class — a starved gate failing closed — stops applying. You can keep using the machine. |
Measured vs estimated, because it matters here. The 24–32 GB row is measured: 15 s to generate, 200–255 s of the project's own tsc and suite, per task, on a 32 GB M2 Pro. The 48–64 GB row is an estimate derived from two
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