Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Pick one movie, show, book, artist or restaurant a whole group will enjoy, using Qloo taste data.
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.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://common-ground.lipmichal.workers.dev/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http common-ground https://common-ground.lipmichal.workers.dev/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"common-ground": {
"url": "https://common-ground.lipmichal.workers.dev/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": {
"common-ground": {
"type": "http",
"url": "https://common-ground.lipmichal.workers.dev/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://common-ground.lipmichal.workers.dev/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
도구 이름과 설명은 서버가 2026년 11월 7일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.
find_common_groundPick ONE movie, TV show, book, music artist, podcast, restaurant (kind=place, with location) or destination that a whole group will enjoy. Give each person's name and 2 to 5 things they love. Favourites can come from another category with tasteFrom, for example music artists to p
plan_night_outPlan dinner, drinks and a live music venue in one city for 2 to 6 friends. Give the city and each friend's name with 1 to 4 music artists, movies, TV shows or books they love. Optionally give an exact night date as YYYY-MM-DD; Qloo then filters venues by that date's weekday only,
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 theluckystrike 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
300ms 만에 응답(HTTP 200)
로그인 필요 없음
도구 설명 2개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 3개 중 3개를 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.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.0)은 11일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Systemdox
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.
Your architecture in your agents' context: checks, specs, ADRs and docs over MCP, at write time.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Plan a night out your whole friend group will love. For friends who argue about where to go. Everyone names a few bands, films, shows or books they love. Qloo's cross-domain taste graph turns that shared taste into dinner, drinks and live music in your city. Each stop names the favourites that picked it and shows how much each friend's taste counts.
Open the live app · MCP endpoint · Live mode check
The earlier 85-second video and screenshots below show the interface before the optional date field. The video also uses older score and time labels. Use the app and the current limits below to assess present behavior.
feature.explainability. The app names the favourites that drove the pick ("Radiohead, Ana, 16%") and splits the pick between friends. When one friend's taste barely counts, the app says so and asks for one more favourite.Below the night planner, "Or pick one thing together" picks one movie, show, book, artist or restaurant the same fair way. No login is needed.
The privacy notice is web/privacy.html in this source. Its public URL becomes available when this version is deployed.
The browser sends the city, optional date, friend names and favourites to the app's Cloudflare Worker. In live mode the Worker sends favourite text unchanged to Qloo search, then matched entity IDs to Qloo Insights, with the city and selected weekday for place and night calls. A city is required when picking a restaurant. Member names are not a separate field in those Qloo request parameters; a name typed into a favourite field is sent as favourite text. The app has no accounts and does not automatically anonymize the text you enter. The app's own web code sets no cookies and loads no analytics script. The Worker has no database binding. The web night API at /api/night can hold a plan in a per-isolate memory cache for up to 30 minutes for reuse. That period is a reuse window, not a deletion time, and entries can remain until eviction or isolate shutdown. The single-pick web API and both MCP tools do not use that cache. Result images are loaded directly from Qloo-supplied URLs, so their host receives ordinary network metadata such as IP address and user agent, and may receive the referring page depending on browser policy. Qloo and Cloudflare process data under their own policies. Their actual retention is not controlled or fully known by this app. The verified public contact is the GitHub issue tracker. Do not put personal data in a public issue.
Both flows are MCP tools on one Streamable HTTP endpoint, plan_night_out and find_common_ground.
claude mcp add --transport http common-ground https://common-ground.lipmichal.workers.dev/mcp
Then ask your agent, for example "Plan a night out in Lisbon. Ana loves Radiohead and Dune, Tom loves Kendrick Lamar and The Bear, Priya loves Phoebe Bridgers and Normal People." plan_night_out takes a city, 2 to 6 members with 1 to 4 likes each, and an optional date in YYYY-MM-DD form. It returns the available stops, the favourites behind each, each friend's share, a call trace and dateScope. A plan can be incomplete if Qloo cannot find all three stops. find_common_ground input is kind, an optional tasteFrom (a category, or any for mixed favourites), an optional location and 2 to 8 members with 2 to 5 likes each. The tool returns the pick, three alternatives, a reason per person and a trace of the Qloo calls.
Registry name io.github.theluckystrike/common-ground in the official MCP registry.
Built for the Qloo Agentic Hackathon by Michael Lip. MIT license.
Use Node.js 22 or later and npm.
npm ci
npm test npm run typecheck npm run dev
Open the local URL printed by Wrangler. Without a key, the app runs on local synthetic fixtures (see below).
For local live mode, place the key in .dev.vars. Use a line with the variable name and your actual value. Keep this file private.
QLOO_API_KEY=YOUR_API_KEY
GET /search resolves each favourite across artists, movies, TV shows and books. Each favourite keeps the type Qloo returns.GET /v2/insights call sends everyone's favourites as signal.interests.entities, filter.type=urn:entity:place, filter.location.query with the city, a stop tag and feature.explainability=true. Stop tags are urn:tag:genre:place:restaurant, urn:tag:category:place:bar and urn:tag:genre:place:live_music_venue.filter.location.radius=0). The app keeps up to 20 real venues. A venue needs opening hours in Qloo and a category that fits the stop, such as a restaurant for dinner. Shops, malls, markets and event rentals are dropped, and so are streets and districts. Dinner prefers restaurants that are not also bars or cafes, and live music prefers music venues that are not also restaurants. Each falls back to mixed venues only when a city has fewer than 3 pure ones. One more Insights call per friend scores that pool with filter.results.entities. With a selected date, every group and per-person venue call also sends Qloo's documented filter.hours weekday value.query.explainability scores name the favourites behind it. When Qloo weighs the favourites about equally, the app says the venue is a balanced compromise instead of showing near-equal percentages. Each friend's share is the sum of their favourites' scores. A shared favourite is split evenly.A four-friend plan makes 8 searches and 15 Insights calls. The same plan within 30 minutes is answered from memory, so replays by judges do not spend the quota. The cache separates each selected calendar date from other dates and from an undated request.
The Worker reads QLOO_API_KEY from its environment. On Cloudflare this value is a Worker secret. The browser never receives the key.
GET /search resolves each favourite with query and types. With tasteFrom, favourites resolve in that category, for example music artists.GET /v2/insights runs separately for each person.filter.type, signal.interests.entities and take=50.filter.location.query and filter.tags=urn:tag:genre:place:restaurant, so museums and stations drop out.query.affinity in the documented zero to one range.filter.results.entities.The key travels only in the X-Api-Key request header. Hackathon calls use https://hackathon.api.qloo.com. Calls time out after five seconds, or nine seconds for explainability calls. A timeout is retried once. Calls are spaced to stay under the hackathon limit of 10 requests per second. A 429 answer is retried twice after one second. Authentication, quota and network errors are reported. A failed live call never switches to fixtures.
See the search reference, Insights reference and hackathon developer guide.
This is for local development only. The hosted app uses live data. Without a key, the same Qloo client reads local synthetic fixtures. The same resolution and fairness code runs in both modes. The page banner, result note, JSON response and MCP response show the mode. Fixture affinities and IDs are invented. They are not evidence of Qloo recommendations or real user preferences. The night plan tests use one small recorded set of real Qloo responses for a Lisbon group, trimmed to IDs, names, types, affinity and explainability.
The fixture file cites the documented response schemas. Search returns success, duration and a results array. Insights returns success and results with entities and duration. Each Insights entity has query.affinity.
The examples cover movies, books, restaurants, artists and TV shows. Only names listed in the fixture catalogue resolve without a key. Unknown names are reported rather than invented. Fixture restaurants are fictional and limited to the Warsaw example. Their names do not imply that a real venue exists.
Authenticate Wrangler with your own Cloudflare account.
npm run deploy
npx wrangler secret put QLOO_API_KEY npm run verify:live -- https://YOUR-WORKER.workers.dev
The secret command prompts for the key. It updates the deployed Worker without storing the key in source. The verification command checks the mode and performs a real group pick. It prints no credentials and stores no Qloo data.
GET /health reports the selected mode and whether a key is configured. A live health response alone proves configuration. A successful live pick confirms that Qloo answered.
Connect a Streamable HTTP MCP client to /mcp on the deployed host. List tools and call find_common_ground with the same input as /api/pick.
{
"kind": "movie", "members": [ { "name": "Ana", "likes": ["Prisoners", "Gone Girl"] }, { "name": "Tom", "likes": ["Interstellar", "Inception"] } ] }
Add "tasteFrom": "artist" to pick a movie from music favourites.
The tool returns structured results and plain text. It is read only and does no
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요