Common Ground

io.github.theluckystrike由 GitHub 帳號 theluckystrike 發布v1.0.0更新於 Nov 6, 2026

Pick one movie, show, book, artist or restaurant a whole group will enjoy, using Qloo taste data.

發布方自己的服務:Ground

已驗證Streamable HTTP可網頁執行位置與生活媒體與設計

概覽

AI 產生的概覽

遠端 MCP 伺服器,透過 Qloo 品味資料替一群人挑出一部電影、影集、書、藝人或餐廳,或規劃晚餐加現場音樂的夜晚行程。

可以做什麼
  • 挑選共同喜好:給定類型(電影、影集、書、藝人、餐廳或目的地)、可選地點和 2 至 8 位成員各 2 至 5 項喜好,回傳一個結果、三個備選、每個人的理由以及 Qloo 呼叫紀錄。
  • 規劃夜晚行程:給定城市、可選日期和 2 至 6 位朋友各 1 至 4 項喜好,回傳晚餐、酒吧和現場音樂場所,以及每個場所背後的喜好和每位朋友的影響力佔比。
  • 跨領域品味:可用某一類別的喜好來挑選另一類別的結果,例如用音樂藝人來選餐廳。
適用情境
適合需要替一群人給出一個公平且可解釋的推薦,並希望看到針對每個人的理由,而不是籠統建議的情況;也適合根據大家在音樂、影視和書籍上的共同品味規劃某個城市的夜晚行程。
執行需求
無需安裝:它是託管在提供方主機上的遠端 Streamable HTTP 端點,以 HTTP 傳輸方式加入,未宣告驗證、環境變數或請求標頭。託管服務使用提供方自己的 Qloo API 金鑰,因此可用性取決於 Qloo 存取權限。
安裝前請注意
唯讀:不會預訂場所或購買媒體。城市、可選日期、朋友姓名和喜好會傳送到提供方的 Cloudflare Worker 並轉給 Qloo,由其依自身政策處理;填入喜好欄位的姓名會當作喜好文字送出,應用程式不會自動匿名化輸入。結果是基於親和度的建議,並非查證過的營業時間、可用性或預訂,且公開端點沒有應用層限流。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Common Ground,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.theluckystrike%2Fcommon-ground/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "common-ground": {
      "type": "http",
      "url": "https://common-ground.lipmichal.workers.dev/mcp"
    }
  }
}

README

Common Ground

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.

[Four friends list music, films, TV and books. Qloo plans dinner, drinks and live music in Lisbon, and each stop names the favourites behind it]

Why it needs Qloo

  • Taste in one domain picks places in another. Nobody in the group names a restaurant or a bar. Ana gives Radiohead and Dune, Tom gives Kendrick Lamar and The Bear. Qloo links that music, film and TV taste to real venues in the city. A search engine or an LLM alone has no per-person score for that link.
  • Qloo says why. Each stop uses Qloo's 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.
  • A real score for every friend. Qloo Insights gives each friend an affinity for every candidate venue. Each stop is the venue whose least happy friend is happiest. Scores are raw Qloo affinity, so real gaps stay visible and close calls are labelled.
  • Nothing is made up. Every favourite is matched with Qloo search. Unknown names are reported, never guessed. A failed live call shows an error, not fake data.

Try it in 30 seconds

  1. Open the live app. "Night in Lisbon" is ready with four friends.
  2. Optionally choose a date, then press Plan our night. A selected date filters venues by its weekday. Exact opening hours and availability are not checked. A request usually takes about 4 to 9 seconds.
  3. Read the three stops. "Picked by" names the favourites behind each venue. "Whose taste counts" shows each friend's share.
  4. Open Show Qloo's work for the live call count and the matched Qloo entities.
  5. Try "Birthday in New York" or "Team night in London", or type your own friends.

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.

[Show Qloo's work panel with the live call count and the per-person score table]

Privacy

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.

Use it from an agent

Both flows are MCP tools on one Streamable HTTP endpoint, plan_night_out and find_common_ground.

sh
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.

Setup

Use Node.js 22 or later and npm.

sh
npm cinpm testnpm run typechecknpm 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.

dotenv
QLOO_API_KEY=YOUR_API_KEY

How Qloo plans the night

  1. GET /search resolves each favourite across artists, movies, TV shows and books. Each favourite keeps the type Qloo returns.
  2. For each stop (dinner, drinks, live music), one 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.
  3. The group call asks for 30 venues inside the city (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.
  4. Each stop is the venue with the highest lowest raw affinity. The group average breaks ties. A venue is used only once in the night.
  5. The winner's 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.

How Qloo drives the single pick

The Worker reads QLOO_API_KEY from its environment. On Cloudflare this value is a Worker secret. The browser never receives the key.

  1. GET /search resolves each favourite with query and types. With tasteFrom, favourites resolve in that category, for example music artists.
  2. GET /v2/insights runs separately for each person.
  3. Each Insights request sends filter.type, signal.interests.entities and take=50.
  4. Restaurant requests also send filter.location.query and filter.tags=urn:tag:genre:place:restaurant, so museums and stations drop out.
  5. The client reads each entity's query.affinity in the documented zero to one range.
  6. The tool pools the top candidates of every person, up to 50 IDs.
  7. A second Insights call per person scores that pool with filter.results.entities.
  8. Each person's scores are divided by their own highest affinity.
  9. A candidate that Qloo does not score for a person gets zero for that person.
  10. The tool removes known favourites and picks the highest minimum score.

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.

Running without a key

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.

Deploy

Authenticate Wrangler with your own Cloudflare account.

sh
npm run deploynpx wrangler secret put QLOO_API_KEYnpm 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.

Agent access

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.

json
{  "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 not book venues or buy media.

Limits

Night plans have two to six friends with one to four favourites each, and need a large enough city. The optional date must be a real calendar date between 1900 and 9999. Its weekday is derived in UTC so the server's timezone cannot change the selected day. Incomplete native date input is rejected before a browser request is sent. Qloo's weekday filter does not verify exact opening hours, holiday schedules, live availability, travel feasibility or event tickets. Suggested stop times are not reservations or a checked itinerary. With no date, there is no opening-day filter. Explainability scores are often close together, so "Picked by" shows influence, not a single cause. The venue check uses Qloo category tags and listed hours. It removes streets, districts, shops and markets, but in a small city a mixed venue, such as a restaurant that is also a bar, can still win.

Groups have two to eight people with different names. Each person supplies two to five favourites. Restaurants require a city and named venues as favourites. Cuisine words are not treated as restaurant entity IDs. Search takes the first result of the requested type. It does not ask users to confirm ambiguous matches.

Each person gets at most 50 candidates. A missing result is treated as zero, which may reflect limited coverage. The method does not score every possible candidate for every person. A second Insights pass scores a shared pool of up to 50 candidates for each person, so a zero minimum is rare. Match scores are relative within each person's returned list. They are not probabilities of enjoyment. Reasons use shared tags when available and a named input otherwise. They are not model-generated explanations of causality.

Restaurant results can still include bars and cafes that Qloo tags as restaurants. A request can make up to 40 searches and 16 Insights calls. The public endpoint has no application rate limiter or persistent cache. Qloo limits can return HTTP 429. The app has no accounts and does not write group profiles to a database. A web night plan can be held in Worker memory as described in the privacy notice. Favourite text and entity IDs are sent to Qloo in live mode. Member names are not a separate Qloo parameter; a name typed as a favourite is sent as favourite text. API availability after the hackathon depends on Qloo access.

Checks

npm test uses fixture responses and fake fetch functions. It never calls Qloo. Night plan tests replay recorded Qloo responses. Tests cover the night plan, explainability shares, one venue per stop, fairness, pool scoring, input errors, auth errors, rate limits, timeout handling, fixture replay and MCP calls. Date checks cover real calendar validation, weekday request parameters, date-separated caching and the real Plan handler's refusal to send incomplete native input. These tests use fixtures; they do not prove a fresh live-provider result.

sh
gitleaks detect --source . --redact --no-bannergitleaks detect --no-git --source . --redact --no-banner

The scan configuration allows only literal guide placeholders and local ignored documentation HTML. MIT covers the source code. Qloo service access and data remain subject to Qloo terms.

來源:README.md,提交 98c783d

工具

2

find_common_ground

Find common ground for a group

Pick 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 pick a restaurant, or any for a mix of artists, movies, TV shows and books. Uses Qloo's taste graph to score every candidate for every person and returns the option that makes the least happy person as happy as possible, with a reason per person.

輸入參數kind必填members必填locationtasteFrom

plan_night_out

Plan a night out for a group of friends

Plan 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. Qloo's cross-domain taste graph turns that shared taste into real venues. Each stop is the venue whose least happy friend is happiest, and Qloo explainability names the favourites behind it, with the share of each friend's taste.

輸入參數city必填members必填

版本歷史

1
  1. v1.0.0最新Oct 29, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

其他 Ground 整合