Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Code changes and unit tests by local MLX models, behind a gate a machine can run.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"sidecrew": {
"command": "npx",
"args": [
"-y",
"sidecrew",
"mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add sidecrew -- npx -y sidecrew mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"sidecrew": {
"command": "npx",
"args": [
"-y",
"sidecrew",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"sidecrew": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"sidecrew",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto lvlrSajjad bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.0) kam vor 43 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Fomu MCP
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Kenya government form guides: checklists, draft letters, eCitizen, Huduma, timelines. Sample data.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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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