Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Local MCP asset intelligence across Unity, Fab, Megascans, Gumroad & Cosmos.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 Tanshaydar 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.5.0)于5天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。
同一分类中有:Spec Driven Development, Remote Desktop Commander, MemberVault MCP by usefulapi
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间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.
List courses; add users to courses, remove course access or delete users in MemberVault.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
This project started because I wanted to prototype a dam.
Nothing serious — a short demo, maybe more if it worked out. Before building anything, I wanted to see what I already owned that could speed it up. So I searched my library for "dam": nothing came back. Of course nothing came back — no asset is *called* a dam. But spread across four packages I already owned were curved concrete meshes, a water system, some rocky terrain. Everything the dam needed. I'd had most of it for years and never once connected the pieces.
That's what ~1,500 assets across two stores did to me when this started — a library that has since grown past 7,500 assets across five ecosystems. Almost all of it from bundles and sales, none of it remembered. And it's not just me — no AI assistant knows either. Ask one for help and it either builds everything from scratch or sends you shopping, while hundreds of dollars of exactly-the-right-thing sits on your disk.
Quartermaster indexes everything you own across the Unity Asset Store, Fab, Quixel Megascans, Gumroad and Leartes Cosmos — locally, on your machine — and serves it to your coding agent over MCP. It's the tool I wished existed that day: ask about a dam, get told you already own curved concrete meshes.
you → "I want to build a dam — what do I have to work with?"
agent → search_owned_assets(...) finds the concrete meshes, water FX, terrain └─ Nordic Coastal Cliff (Quixel) · 5785 px/m · 2.03 × 2.92 × 2.44 m maps: Basecolor, Normal, Displacement, Cavity, AO, Roughness… validate_stack([...]) checks none of them fight each other import_asset_to_project(...) unpacks into Assets/, demos stripped
Every result is something you own or can claim free — nothing is invented.
*Typing a description, not a name — none of those results share a word with the query.*
Why *Quartermaster*? A quartermaster's job was never remembering what's in stores — it's making sure you're equipped when it's time to move. That's nearer the real problem than forgetting is. I hadn't lost anything; I knew I owned *stuff*. What I couldn't do was get from "I want to prototype a dam" to "open these four packages" without an hour of digging first — and *maybe more if it worked out* doesn't survive an hour of digging. Ideas that arrive that way don't get rejected. They just quietly don't happen, and you never find out whether they would have.
| Source | What comes in | How |
|---|---|---|
| Unity Asset Store | Owned packages, descriptions, gallery art | Authenticated harvest |
| Fab (Epic) | Owned Unreal and Unity listings | Authenticated harvest |
| Quixel Megascans / Megaplants | The catalog, with texel density, scan area and map lists | Public catalog sync |
| Gumroad | Owned products | Authenticated harvest |
| Leartes Cosmos | Owned and claimable Cosmos inventory, with deep screenshot galleries (18 on average, up to 71) | Authenticated harvest |
Everything lands in one SQLite table behind one search surface, so a query crosses all of them at once. Nothing is engine-scoped: a Megascans surface and a Unity shader come back from the same question if they both answer it.
Neither store will admit what you own.
Unity removed /account/purchases (404 since August 2026). Fab has no ownership API, no export button, nothing. Your purchase history exists only inside their private GraphQL, behind SSO, MFA, and bot detection.
Getting at it took four attempts, three of them failures:
That trick is most of this project. The rest — search, linting, unpacking — is honestly straightforward by comparison.
Two hard-won rules baked into the design, if you ever hack on this yourself:
taskkill without /F). An abrupt kill loses Unity's device-trust cookie and you'll get MFA-challenged on every future session.Fab's library view and the Megascans catalog are not the same list, and there is no export that reconciles them — you can hold rights to far more Megascans content than your library page displays. Whatever the cause, the practical result is the same: scrolling and hand-searching for something you already have.
Quartermaster sidesteps it. It syncs the Quixel Megascans and Quixel Megaplants seller catalogs from Fab directly — 5,580 listings as of this writing — independently of what your library view shows, and files them next to everything else you own, tagged by status:
Both are searchable, and every result says which it is, so an agent can tell "you own this" from "you can have this for nothing" without guessing.
Megascans rows also carry their physical specs where the listing publishes them — texel density, scan area, and the map list (basecolor, normal, displacement, cavity, AO, roughness…). That is the difference between an agent telling you it found a rock and an agent telling you it found a 1×1 m scan at 8192 px/m with displacement — which is the part that decides whether it's usable.
python -m src.store_client sync-quixel # catalog
python -m src.store_client enrich-quixel # texel density, scan area, maps
Search that understands intent & vision. This is the dam problem.
BAAI/bge-small-en-v1.5) — *"concrete structures for holding back water"* surfaces meshes and shaders whose listings never mention dams.Qdrant/clip-ViT-B-32) — searching *"gothic cathedral"* literally scores your screenshots and promo renders, finding assets even when their text descriptions are completely silent. A visual hit also hands back *which* screenshot matched, not just the cover art.match field — keyword, semantic+vision, keyword+semantic+vision — so you and your agent can see which signal fired. A pure-vision hit on a listing with useless marketing copy is a different kind of result than an exact title match, and it should be legible as one.docs/concepts.md.All three signals are fused with 3-way Reciprocal Rank Fusion (RRF) on your CPU. No GPU, no vector database process, no cloud API — ONNX Runtime and a numpy matrix, in the same process as everything else.
Measured on a ~7,500-asset vault: ~520 MB peak RAM with both models resident, ~1.4 s for the first query (loading BGE and CLIP), ~85 ms warm after that. The models load lazily, so an agent that never searches never pays for them.
Ground truth about your disk. Scans %APPDATA%/Unity/Asset Store-5.x/ and Epic's VaultCache so every result knows whether it's already downloaded or cloud-only. Agents prefer what's local — a zero-download import beats a 4 GB one.
A linter for stacks. Two vegetation renderers will fight. A MicroSplat module without core MicroSplat silently does nothing. A URP-only shader in an HDRP project renders pink. Quartermaster catches these before you spend an afternoon on them.
Direct unpacking. Extracts cached .unitypackage files straight into Assets/, dropping /Demo/, /Samples/, /Documentation/ and PDFs on the way in — typically 60–80% less bloat per package. Every declared path is normalized and asserted inside /Assets/; escapes are structurally impossible, not just filtered.
The standalone bundle — download Quartermaster-windows-x64.zip from Releases, unzip anywhere. No Python required.
Quartermaster.exe — Desktop GUI with Win+Alt+V spotlight search, store harvesting, library browsing, and direct unpacking.Quartermaster-mcp.exe — Standalone MCP stdio server for Claude Desktop, Cursor, Antigravity, and Windsurf.Your library data lives safely in %LOCALAPPDATA%\Quartermaster, so upgrades are simple folder replacements with zero data loss.
From source — needs Python 3.10+.
git clone https://github.com/Tanshaydar/Quartermaster.git
cd Quartermaster pip install -r requirements.txt
Seed your library:
1. Sign in. The one step that needs you. A normal browser window opens; 2FA and captchas behave exactly as they always do. Close it when you're done and the session persists locally.
python -m src.store_client login unity
python -m src.store_client login fab python -m src.store_client login gumroad # optional python -m src.store_client login cosmos # optional — Leartes Cosmos
2. Harvest and enrich. Long-running, resumable, safe to re-run — each picks up where it stopped.
python -m src.store_client fetch unity
python -m src.store_client fetch fab python -m src.store_client fetch gumroad # if you signed in above python -m src.store_client fetch cosmos # if you signed in above python -m src.store_client sync-quixel # Megascans/Megaplants catalog — no login needed python -m src.store_client enrich # descriptions and cover art, politely batched python -m src.store_client enrich-quixel # Megascans scan specs python -m src.store_client fab-deep-media # Fab only: plain HTTP is 403'd, galleries need the authed browser
**3. Build the local indexes, then scan your
只显示了开头部分;其余内容请在仓库中阅读