Delightful's Game Research Starter Pack

Where to look for games industry research: 873 sources across ten markets, cited and free.

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컨텍스트 비용

~1,987토큰 (도구 정의)
~2.6 KB일반적인 응답 크기
중간 정도의 주의 영향 (128k 컨텍스트의 1.55%)

이는 서버의 도구가 모델의 컨텍스트에 로드될 때마다 소비되는 대략적인 토큰 수입니다. 수치가 높을수록 다른 작업에 사용할 수 있는 주의가 줄어듭니다.

설치

원클릭 설치

`claude_desktop_config.json` 파일에 다음을 추가하세요:

{
  "mcpServers": {
    "games-research-starter-pack": {
      "url": "https://games.thisisdelightful.com/mcp"
    }
  }
}

원격 엔드포인트

https://games.thisisdelightful.com/mcpstreamable-http

할 수 있는 일

도구 목록

도구 (6)

🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢search_sources(query, market, group, medium, language, ...)

Search 924 curated sources on the video games industry: press outlets, trade associations, datasets, analysts, podcasts, books, YouTube channels and communities across 26 markets. Every one was opened and read before it was described, and each result says what it lets you find out, who owns it and what it costs. This answers "where would I look for this?" — it is a directory of sources, not a source of facts, and nothing in it is ranked or scored.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Free text, matched against the name, the description and the owner. All words must appear. Omit to browse a filter instead."
    },
    "market": {
      "type": "string",
      "enum": [
        "US",
        "Global",
        "JP",
        "KR",
        "Not market specific",
        "UK",
        "DE",
        "FR",
        "CN",
        "MENA",
        "IT",
        "SEA",
        "CA",
        "Nordics",
        "BR",
        "IN",
        "MX",
        "ES",
        "TR",
        "NL",
        "AU",
        "PL",
        "TW",
        "EU",
        "LATAM",
        "Asia",
        "BE"
      ],
      "description": "Market code. US, JP, KR, UK, DE, FR, CN, MENA, IT, CA have full profiles behind them; SEA, Nordics, BR, IN, MX, ES, TR, NL, AU, PL, TW, EU, LATAM, Asia, BE only tag sources. Global means the source covers everything, and \"Not market specific\" means market is not its axis."
    },
    "group": {
      "type": "string",
      "enum": [
        "Press",
        "Media",
        "Institutions",
        "Data",
        "Communities",
        "People"
      ],
      "description": "Broad kind of source."
    },
    "medium": {
      "type": "string",
      "enum": [
        "News outlet",
        "Organisation",
        "Forum or community",
        "Video channel",
        "Person",
        "Data tool",
        "Podcast",
        "Book or paper",
        "Company disclosure",
        "Report or document",
        "Newsletter",
        "Research firm",
        "Link list"
      ],
      "description": "What form it takes."
    },
    "language": {
      "type": "string",
      "enum": [
        "English",
        "Japanese",
        "Korean",
        "German",
        "French",
        "Spanish",
        "Portuguese",
        "Arabic",
        "Italian",
        "Chinese",
        "Turkish",
        "Dutch",
        "Polish",
        "Traditional Chinese",
        "Bahasa Indonesia",
        "Multilingual",
        "Swedish",
        "Vietnamese",
        "Finnish",
        "Danish",
        "Norwegian",
        "Thai",
        "Hindi",
        "Indonesian",
        "Malay"
      ],
      "description": "The language you would be reading it in."
    },
    "cost": {
      "type": "string",
      "enum": [
        "Free",
        "Paid",
        "Freemium",
        "Unknown"
      ],
      "description": "Recorded on 534 of 924 rows — the press outlets and the individual people are not priced, so filtering on this excludes them rather than reporting them as not free."
    },
    "offset": {
      "type": "number",
      "description": "Rows to skip before the first one returned, for paging. Default 0. The note on each page says what to pass for the next."
    },
    "limit": {
      "type": "number",
      "description": "Rows per page, default 20, maximum 50. A page is the next rows in file order, never the top ones — nothing here is ranked."
    }
  },
  "additionalProperties": false
}
🟢get_source(slug)

Retrieve one source by its slug, with everything recorded about it. Slugs come back from search_sources and are permanent — the same slug names the same source across releases, so it is what to cite.

입력 스키마

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Permanent identifier, e.g. \"sensor-tower\"."
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}
🟢get_market(code)

How to research one of 10 games markets, and the profile behind it. It opens with before_you_start, the research notes for that market: which national annuals are paid and what is free, which venues are closed or could not be verified, which figures overlap or are published on a basis that will not compare, what a weekly chart does and does not count. Then known_gaps, what the directory does not hold for that market and where to go instead. Then a sourced narrative built from claims that each carry the link they came from, a market-size figure with the basis it was published on, a player-population figure with the definition of who was counted, and where that market's data lives. Only these ten have profiles — for any other market code, search_sources with a market filter is what exists.

입력 스키마

{
  "type": "object",
  "properties": {
    "code": {
      "type": "string",
      "enum": [
        "US",
        "JP",
        "KR",
        "UK",
        "DE",
        "FR",
        "CN",
        "MENA",
        "IT",
        "CA"
      ],
      "description": "Market code."
    }
  },
  "required": [
    "code"
  ],
  "additionalProperties": false
}
🟢list_trends(query, market, stage, category, slug, ...)

The 38 conversations currently moving the games industry, each with what it is, why it matters, the markets it lands in, its stage, how old the row is, and dated further reading on request. A routing map rather than a synthesis: it names arguments and points at where they are happening, and takes no position on any of them. Filter by market, stage, category or a free-text query; every filter narrows the list and none of them orders it. Rows come 14 to a page: page with offset, or name one by slug to read it with its further reading. This is the fastest-decaying data here — every row is dated, and anything older than about six months needs a refresh.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Free text, matched against the name, what it is, why it matters, where to follow it, its category and the titles of its further reading. All words must appear. A word filter, not a semantic search: \"layoffs\" finds the layoff trend, a synonym the rows never use finds nothing. Omit to browse a filter instead."
    },
    "market": {
      "type": "string",
      "enum": [
        "US",
        "Global",
        "JP",
        "KR",
        "Not market specific",
        "UK",
        "DE",
        "FR",
        "CN",
        "MENA",
        "IT",
        "SEA",
        "CA",
        "Nordics",
        "BR",
        "IN",
        "MX",
        "ES",
        "TR",
        "NL",
        "AU",
        "PL",
        "TW",
        "EU",
        "LATAM",
        "Asia",
        "BE"
      ],
      "description": "Trends that reach this market: tagged to it directly, reached through an EU tag, or global. Each row then says which, in market_relevance, and the list comes back closest first. Most trends in games are global and apply everywhere."
    },
    "stage": {
      "type": "string",
      "enum": [
        "Dominant",
        "Emerging",
        "Perennial",
        "Receding"
      ],
      "description": "Dominant is sustained mainstream coverage for a year or more. Emerging is real and accelerating. Perennial recurs cyclically. Receding was dominant and is cooling, kept so dated coverage is recognisable as dated."
    },
    "category": {
      "type": "string",
      "enum": [
        "Money & business model",
        "Regulation, safety & age",
        "Platform & distribution",
        "Culture & audience",
        "Geography & power",
        "Technology"
      ]
    },
    "slug": {
      "type": "string",
      "description": "One trend by its permanent slug, as a list returns it. Comes back with its further reading unless include_further_reading says otherwise. The other filters are ignored when this is set."
    },
    "include_further_reading": {
      "type": "boolean",
      "description": "Default false, and true when slug is given. Further reading roughly doubles a row, so at most 10 rows travel with it; ask for a row by slug to read one in full."
    },
    "offset": {
      "type": "number",
      "description": "Rows to skip before the first one returned, for paging. Default 0. The note on each page says what to pass for the next."
    },
    "limit": {
      "type": "number",
      "description": "Rows per page, default 14, at most 38 without further reading and 10 with it. A page is the next rows in the order described, never the top ones — nothing here is ranked."
    }
  },
  "additionalProperties": false
}
🟢get_landscape(kind)

The platform and genre maps. 35 platforms — storefronts, consoles, livestreaming and UGC — with who owns each and where its data lives. 30 genres with definitions, subgenres, example games, and the terms actually used in Chinese, Korean and Japanese. Read the genre map before comparing two datasets: the industry has no shared taxonomy and this records where the vendors disagree.

입력 스키마

{
  "type": "object",
  "properties": {
    "kind": {
      "type": "string",
      "enum": [
        "platforms",
        "genres"
      ],
      "description": "Which map."
    }
  },
  "required": [
    "kind"
  ],
  "additionalProperties": false
}
🟢search_techniques(market, query)

39 search techniques for games research, each with a query you can paste, what it surfaces and why it works. Includes local-language strategies for researching the Japanese, Korean and Chinese markets without reading the language. Use this before searching the open web on a games question — these are the queries that reach material a plain search buries.

입력 스키마

{
  "type": "object",
  "properties": {
    "market": {
      "type": "string",
      "enum": [
        "US",
        "Global",
        "JP",
        "KR",
        "Not market specific",
        "UK",
        "DE",
        "FR",
        "CN",
        "MENA",
        "IT",
        "SEA",
        "CA",
        "Nordics",
        "BR",
        "IN",
        "MX",
        "ES",
        "TR",
        "NL",
        "AU",
        "PL",
        "TW",
        "EU",
        "LATAM",
        "Asia",
        "BE"
      ],
      "description": "Techniques for this market, plus the ones that apply everywhere."
    },
    "query": {
      "type": "string",
      "description": "Your question in your own words, for example \"what are Japanese players saying about a launch\". Techniques are ranked by how many of its words they mention, so a whole question works better than one keyword."
    }
  },
  "additionalProperties": false
}

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