glim.sh

Give your agent live data from Twitter, Reddit, the web and GitHub. No API keys, no scraping stack.

사용해야 할까요

품질 및 안전성

A
설명 품질
100%
스키마 완전성
99%
이름 품질
80%
오염 위험
60%
권한 일치
100%
프로토콜 준수
100%

발견 사항 (3)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool description contains URL to non-standard domainglim_twitter_get에서
  • LOWTool description contains role marker that could confuse chat modelsglim_github_search에서

도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.

컨텍스트 비용

~6,820토큰 (도구 정의)
~3.7 KB일반적인 응답 크기
상당한 주의 영향 (128k 컨텍스트의 5.33%)

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": {
    "glim": {
      "url": "https://glim.sh/mcp"
    }
  }
}

원격 엔드포인트

https://glim.sh/mcpstreamable-http

할 수 있는 일

도구 목록

도구 (14)

🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢glim_twitter_search(query, sort, cursor, start_date, end_date, ...)

Search Twitter/X. Returns a compact human-readable list by default; pass format='json' for full structured data. Use glim_twitter_get(ref) for full thread context. Use docs://search-operators for reference.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search query with operators (e.g. 'from:elonmusk AI min_faves:100 within_time:7d')"
    },
    "sort": {
      "description": "Sort by relevance or recency: \"top\" (most engaged tweets matching the query - best for \"what's the conversation about X\") or \"latest\" (newest first - best for monitoring/recency). Default: \"top\".",
      "type": "string",
      "enum": [
        "latest",
        "top"
      ]
    },
    "cursor": {
      "description": "Pagination cursor from previous search. Ranking is strongest on page 1 - paged results under sort:'top' trend toward recency (upstream behavior).",
      "type": "string"
    },
    "start_date": {
      "description": "Only tweets on or after this time. YYYY-MM-DD (UTC midnight) or ISO 8601 datetime with Z/offset (e.g. 2026-04-13T14:30:00Z)",
      "type": "string",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}(T\\d{2}:\\d{2}(:\\d{2}(\\.\\d+)?)?(Z|[+-]\\d{2}:?\\d{2}))?$"
    },
    "end_date": {
      "description": "Only tweets before this time. YYYY-MM-DD (inclusive through end of day UTC) or ISO 8601 datetime with Z/offset (e.g. 2026-04-13T14:30:00Z)",
      "type": "string",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}(T\\d{2}:\\d{2}(:\\d{2}(\\.\\d+)?)?(Z|[+-]\\d{2}:?\\d{2}))?$"
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    },
    "expand_urls": {
      "default": false,
      "description": "When true, auto-crawl entity URLs and attach crawled_content to tweets. Off by default: responses can grow by up to 4KB per expanded URL. Use glim_web_fetch(url) for targeted crawls instead.",
      "type": "boolean"
    }
  },
  "required": [
    "query"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_twitter_get(ref, include, include_replies, include_mentions, cursor, ...)

Fetch a tweet or a user from one reference. A tweet URL (incl. handle-less /i/status/<id>) returns the tweet with full thread context, parent, and optional replies/quotes; a profile URL (https://x.com/<handle>) returns the user with recent tweets. Prefer full URLs - if you only have a numeric id, pass it as a quoted string. Returns a compact human-readable view by default; pass format='json' for full structured data.

입력 스키마

{
  "type": "object",
  "properties": {
    "ref": {
      "type": "string",
      "description": "Tweet URL or profile URL. A tweet URL (incl. /i/status/<id>) returns the tweet + thread; a profile URL (https://x.com/<handle>) returns the user + recent tweets. Prefer full URLs - if you only have a numeric id, pass it as a quoted string."
    },
    "include": {
      "description": "Tweet refs only: also fetch 'replies' and/or 'quotes'",
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "replies",
          "quotes"
        ]
      }
    },
    "include_replies": {
      "default": false,
      "description": "Profile refs only: include replies in the timeline",
      "type": "boolean"
    },
    "include_mentions": {
      "default": false,
      "description": "Profile refs only: include the mentions timeline",
      "type": "boolean"
    },
    "cursor": {
      "description": "Profile refs only: pagination cursor from next_cursor",
      "type": "string"
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    },
    "expand_urls": {
      "default": false,
      "description": "When true, auto-crawl entity URLs and attach crawled_content to tweets. Off by default: responses can grow by up to 4KB per expanded URL. Use glim_web_fetch(url) for targeted crawls instead.",
      "type": "boolean"
    }
  },
  "required": [
    "ref"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_reddit_search(query, sort, time, limit, cursor, ...)

Search Reddit posts. Each result comes with full post content and its top comments, so a single search usually answers the question without follow-up. Compact human-readable text by default; pass format='json' for full structured data. Use glim_reddit_get(ref) for a single post's complete comment tree. Page with cursor (response gives next_cursor when more exist). See docs://reddit-search.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search query (e.g. 'subreddit:programming machine learning')"
    },
    "sort": {
      "default": "relevance",
      "description": "Sort order. Keep 'relevance' (default) for question or topic queries - it ranks by how well posts match your query. 'top'/'hot' rank by score/recency and largely ignore the query text, so use them only to browse what's popular in a subreddit.",
      "type": "string",
      "enum": [
        "relevance",
        "hot",
        "top",
        "new",
        "comments"
      ]
    },
    "time": {
      "default": "all",
      "description": "Time range",
      "type": "string",
      "enum": [
        "hour",
        "day",
        "week",
        "month",
        "year",
        "all"
      ]
    },
    "limit": {
      "default": 10,
      "description": "Max posts (1-10), each with full content + top comments",
      "type": "integer",
      "minimum": 1,
      "maximum": 10
    },
    "cursor": {
      "description": "Pagination cursor from a prior response's next_cursor",
      "type": "string",
      "maxLength": 64,
      "pattern": "^\\s*(?:[tT]\\d_)?[a-zA-Z0-9]+\\s*$"
    },
    "start_date": {
      "description": "Only posts on or after this date (YYYY-MM-DD)",
      "type": "string"
    },
    "end_date": {
      "description": "Only posts before this date (YYYY-MM-DD)",
      "type": "string"
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "query"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_reddit_get(ref, comment_sort, comment_limit, comment_depth, sort, ...)

Fetch a Reddit post, subreddit, or user by ref. Posts return comments; subreddits and users return profile metadata plus recent activity.

입력 스키마

{
  "type": "object",
  "properties": {
    "ref": {
      "type": "string",
      "description": "Post ID or URL, subreddit ref (r/programming or reddit.com/r/programming), or user ref (u/spez or reddit.com/user/spez)"
    },
    "comment_sort": {
      "default": "confidence",
      "description": "Comment sort. Post refs only: subreddit/user listings always hydrate a fixed 2 top-level comments sorted by top.",
      "type": "string",
      "enum": [
        "confidence",
        "top",
        "new",
        "controversial",
        "old",
        "qa"
      ]
    },
    "comment_limit": {
      "default": 50,
      "description": "Max comments (post refs only)",
      "type": "integer",
      "minimum": 0,
      "maximum": 200
    },
    "comment_depth": {
      "default": 5,
      "description": "Max nesting depth (post refs only)",
      "type": "integer",
      "minimum": 0,
      "maximum": 10
    },
    "sort": {
      "default": "hot",
      "description": "Listing post sort",
      "type": "string",
      "enum": [
        "hot",
        "new",
        "top",
        "rising"
      ]
    },
    "time": {
      "default": "day",
      "description": "Listing time range",
      "type": "string",
      "enum": [
        "hour",
        "day",
        "week",
        "month",
        "year",
        "all"
      ]
    },
    "limit": {
      "default": 10,
      "description": "Max subreddit posts (1-10), each with full content + top comments",
      "type": "integer",
      "minimum": 1,
      "maximum": 10
    },
    "cursor": {
      "description": "Pagination cursor from a prior subreddit response's next_cursor",
      "type": "string",
      "maxLength": 64,
      "pattern": "^\\s*(?:[tT]\\d_)?[a-zA-Z0-9]+\\s*$"
    },
    "include_posts": {
      "default": true,
      "description": "Include recent posts for user refs",
      "type": "boolean"
    },
    "include_comments": {
      "default": false,
      "description": "Include recent comments for user refs",
      "type": "boolean"
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "ref"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_web_search(query, include_domains, exclude_domains, published_within_days, format)

Semantic web search powered by Exa. Returns titles, URLs, and the top query-relevant excerpt per result. Compact text by default; pass format='json' for full structured data incl. all excerpts per result. Use glim_web_fetch(url) for full page content. Matching is semantic, so a query with no real match still returns ten nearest-neighbour results rather than zero - judge relevance from the excerpts, not from the result count.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search query"
    },
    "include_domains": {
      "description": "Restrict results to these domains (e.g. ['arxiv.org'])",
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "exclude_domains": {
      "description": "Exclude results from these domains. Useful for filtering noisy aggregators or SEO farms when you've seen them dominate results (e.g. ['pinterest.com', 'quora.com']).",
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "published_within_days": {
      "description": "Restrict to results published within the last N days. Skip this for broad queries - it excludes pages without publish-date metadata. Common values: 1, 7, 30, 365.",
      "type": "integer",
      "minimum": 1,
      "maximum": 3650
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable list, fewer tokens. 'json': the same results as structured data (title, url, snippet, score, published_date, author).",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "query"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_web_fetch(url, format, selector)

Fetch a single web page and extract clean content. Auto-tier server-side: handles SSR (Next.js, Nuxt, TikTok, Pinterest, YouTube), SPA shells, PDFs, paywall detection, residential-proxy escalation, and stealth profiles for TikTok / Instagram / Pinterest / YouTube. Returns clean markdown (default) with a YAML frontmatter header (url, outcome, total_chars). Read 'outcome' to classify the result (success | teaser | thin_content | paywall | bot_challenge | consent_wall | login_wall | rate_limited | timeout | transient_upstream | unsupported_target | not_found | error). Large pages (>80k chars) are truncated inline with truncated_chars + a download_full_url to the complete extraction (expires ~1h). Permanently unsupported (outcome=unsupported_target, cost=0 upstream): Bluesky search, Instagram post/reel and tag/explore pages (profiles work), Pinterest search, g2.com, Truth Social, Xiaohongshu. Threads and Instagram profile pages ARE supported.

입력 스키마

{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "description": "URL to fetch"
    },
    "format": {
      "default": "markdown",
      "description": "Output format. 'markdown' (default) clean article text; 'html' raw cleaned HTML; 'json' the structured SSR blob (TikTok / Pinterest / YouTube) instead of article text.",
      "type": "string",
      "enum": [
        "markdown",
        "html",
        "json"
      ]
    },
    "selector": {
      "description": "CSS selector to scope the result. An anchor-id selector (e.g. a docs anchor like '#usage') that lands on a heading expands to its whole section; other selectors return the matched elements themselves.",
      "type": "string"
    }
  },
  "required": [
    "url"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_github_search(query, kind, repo, page, per_page, ...)

Search GitHub repositories, conversations (issues+PRs), discussions, or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. kind='discussions': GitHub Discussions, a SEPARATE index from issues/PRs - a question answered there never appears under conversations, so reach for it when a repo does its Q&A in Discussions; supports repo:/org:/author:/is:answered plus category: (the repo's own category name, needs a repo: scope), up to 10 results per page, no sort:. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:answered/category: -> discussions, is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos); a conversations search with no matches is retried as discussions and says so. Returns compact text by default; pass format='json' for full structured data.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search query in full GitHub search syntax: qualifiers (repo:owner/name, org:/user:, language:, path: with globs, symbol:, content:, is:, stars:>N, label:, sort:stars), boolean AND/OR/NOT with parentheses, \"exact strings\", and /regex/. kind=repos: minimal distinctive keywords - the project/library name (GOOD: 'rtk', 'react query'; BAD: 'rtk rust token killer' - every extra word must ALL match and buries the real repo; filter with qualifiers, not prose). kind=code: ONE literal code pattern as it appears in files ('useState('), an \"exact string\", a /regex/, or symbol:name for definitions; narrow with repo:/language:/path:, not extra words. kind=conversations: keywords plus filters (is:issue, label:bug). kind=discussions: keywords plus repo:/org:/author:/is:answered/category: - a separate GitHub index from issues/PRs, so a thread that lives in Discussions is invisible to kind=conversations (and vice versa). category: matches the repo's own category name (Ideas, Q&A) and needs a repo: scope; sort: does not apply. Caution: sort: REPLACES relevance ranking (sort:reactions = most-popular thread mentioning the words anywhere, incl. comments) - omit sort: for best-match. Not supported in code search: license:, enterprise:, is:vendored, is:generated."
    },
    "kind": {
      "description": "What to search: 'repos', 'conversations' (issues+PRs), 'discussions' (GitHub Discussions - a separate index from issues/PRs), or 'code' (literal/regex/symbol search across 2.8M+ public GitHub repos). Optional - inferred from the query: is:answered/category: implies discussions, is:/label:/author: implies conversations, path:/symbol:/content://regex/ implies code, stars:/topic:/in:readme implies repos, otherwise repos. type:code / type:repos / type:discussions in the query also works. A conversations search that matches nothing is retried as discussions, so an answer that lives in Discussions is not silently missed.",
      "type": "string",
      "enum": [
        "repos",
        "conversations",
        "code",
        "discussions"
      ]
    },
    "repo": {
      "description": "Scope to one repository. Accepts 'owner/name', a github.com URL, or a partial 'owner/' (code). Works with any kind; setting it with kind=repos routes the search to conversations, since repo-name search can't scope to one repo. Equivalent to a repo: qualifier in the query (if both are given they must match).",
      "type": "string"
    },
    "page": {
      "description": "Page number",
      "default": 1,
      "type": "integer",
      "minimum": 1,
      "maximum": 10
    },
    "per_page": {
      "description": "Results per page",
      "default": 20,
      "type": "integer",
      "minimum": 1,
      "maximum": 30
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable previews, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "query"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_github_get(ref, page, per_page, format)

Fetch GitHub data from a single ref. GitHub URL or 'owner/repo' shorthand. A repo URL or owner/repo returns metadata + README; /pull/N -> PR (with comments + changed files), /issues/N -> issue, /discussions/N -> discussion (with threaded replies), /blob/<ref>/<path> -> file (raw.githubusercontent.com URLs work too), /tree/<ref>[/<path>] -> file tree (optionally scoped to a subdirectory), /commit/<sha> -> one commit with diff, /commits[/<ref>/<path>] -> history (optionally for one file), /branches, /releases (or /releases/tag/<tag> | /releases/latest -> one release), /topics/<name> -> top repos with that topic (by stars).

입력 스키마

{
  "type": "object",
  "properties": {
    "ref": {
      "type": "string",
      "minLength": 1,
      "maxLength": 2048,
      "description": "GitHub URL or 'owner/repo' shorthand. A repo URL or owner/repo returns metadata + README; /pull/N -> PR (with comments + changed files), /issues/N -> issue, /discussions/N -> discussion (with threaded replies), /blob/<ref>/<path> -> file (raw.githubusercontent.com URLs work too), /tree/<ref>[/<path>] -> file tree (optionally scoped to a subdirectory), /commit/<sha> -> one commit with diff, /commits[/<ref>/<path>] -> history (optionally for one file), /branches, /releases (or /releases/tag/<tag> | /releases/latest -> one release), /topics/<name> -> top repos with that topic (by stars)."
    },
    "page": {
      "description": "Page number",
      "default": 1,
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    },
    "per_page": {
      "description": "Results per page",
      "default": 30,
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    },
    "format": {
      "default": "text",
      "description": "Output encoding. 'text' (default): compact human-readable text, fewer tokens (file returns raw content). 'json': machine-readable JSON.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "ref"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_amazon_search(query, category_slug, tld, page, format, ...)

Pass exactly ONE of {query} or {category_slug}. Searches Amazon (com|co.uk|de|fr|es|it) and returns ranked hits with buybox price (gross + VAT-excluded net), ratings, review counts, and ASINs. Drill down with glim_amazon_get(ref). Set sort_by='most_reviewed' (with min_reviews to filter junk) for a trust-weighted re-rank within the current page. Compact text by default; pass format='json' for full structured data.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "description": "Free-text keyword query (mutually exclusive with category_slug)",
      "type": "string"
    },
    "category_slug": {
      "description": "Amazon bestsellers category slug, e.g. 'electronics' (.com), 'elektronik' (.de), 'electronique' (.fr). Invalid slugs return 'not_found' - retry with a correct slug.",
      "type": "string"
    },
    "tld": {
      "default": "com",
      "type": "string",
      "enum": [
        "com",
        "co.uk",
        "de",
        "fr",
        "es",
        "it"
      ],
      "description": "Amazon marketplace: com | co.uk | de | fr | es | it"
    },
    "page": {
      "default": 1,
      "description": "Page number (1-20)",
      "type": "integer",
      "minimum": 1,
      "maximum": 20
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': the same hits as machine-readable JSON. Text already carries every field except `image_url`, which only json returns.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    },
    "sort_by": {
      "description": "Server-side sort, except 'most_reviewed' which re-ranks the current page client-side by review count desc (rating tiebreaker). Pair 'most_reviewed' with min_reviews to skip thinly-reviewed items.",
      "type": "string",
      "enum": [
        "most_recent",
        "price_low_to_high",
        "price_high_to_low",
        "featured",
        "average_review",
        "bestsellers",
        "most_reviewed"
      ]
    },
    "min_reviews": {
      "description": "Drop hits with fewer than N reviews. Pair with sort_by='most_reviewed' for a trust-weighted result. Applied client-side to organic/paid/suggested.",
      "type": "integer",
      "minimum": 0,
      "maximum": 9007199254740991
    },
    "include_paid": {
      "default": false,
      "description": "Include sponsored ad results (default: dropped)",
      "type": "boolean"
    },
    "include_suggested": {
      "default": false,
      "description": "Include 'people also searched for' suggestions (default: dropped)",
      "type": "boolean"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_amazon_get(ref, format)

Fetch Amazon product detail from a full product URL (the marketplace - com|co.uk|de|fr|es|it - is read from the URL host; pass the url field from a glim_amazon_search result, or any /dp/<ASIN> page URL). Returns title, buybox price (gross + VAT-excluded net), stock, delivery estimate, rating, top reviews, and an 'other sellers' summary (count + floor price). Text mode (default) returns a compact view with offers_summary {buybox, lowest_new, lowest_used} - pass format='json' for full structured data incl. the offers[] listing and images.

입력 스키마

{
  "type": "object",
  "properties": {
    "ref": {
      "type": "string",
      "minLength": 1,
      "description": "Full Amazon product URL - pass the `url` from a glim_amazon_search result, or any /dp/<ASIN> product page URL. The URL carries the marketplace (amazon.de, amazon.co.uk, ...), so no separate region is needed; tracking junk in the URL is ignored. A bare ASIN is rejected: it is ambiguous across marketplaces."
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': the same product as machine-readable JSON, plus the fields text omits: the full `offers[]` list (text summarizes it), `images[]`, and variation/other-seller detail.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "ref"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_youtube_get(ref, language_code, origin, format)

Fetch a YouTube video transcript from a video URL or 11-char id. The transcript is cleaned server-side: deduplicated, tags/HTML stripped, with coarse [m:ss] timestamps - roughly a tenth the size of the raw captions. Default format='text' returns it inline (when it fits ~40K chars / ~10K tokens) so a single call gives you the text directly; long-form videos fall back to a download_url note. Pass format='json' for the same transcript plus transcript metadata (video_id, canonical url, language, origin, size) and a presigned download_url - for batch/programmatic use. Default origin='uploader_provided' (human captions); falls back to 'auto_generated' automatically if missing (counts as 2 upstream calls). Cached 7 days server-side.

입력 스키마

{
  "type": "object",
  "properties": {
    "ref": {
      "type": "string",
      "minLength": 1,
      "description": "YouTube video URL or 11-char video id (e.g. https://youtu.be/dQw4w9WgXcQ, https://www.youtube.com/watch?v=dQw4w9WgXcQ, or dQw4w9WgXcQ)"
    },
    "language_code": {
      "default": "en",
      "description": "ISO 639-1 language code (e.g. 'en', 'de', 'fr')",
      "type": "string",
      "minLength": 2,
      "maxLength": 10
    },
    "origin": {
      "default": "uploader_provided",
      "description": "'uploader_provided' for human captions (default), 'auto_generated' for YouTube auto-captions.",
      "type": "string",
      "enum": [
        "uploader_provided",
        "auto_generated"
      ]
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): the cleaned transcript inline as plain text (omitted with a download_url note when it exceeds the ~40K-char inline cap). 'json': the same cleaned transcript plus transcript metadata (video_id, canonical url, language, origin, size) and a presigned download_url - for batch/programmatic use. Both formats return the identical cleaned, deduplicated transcript.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "ref"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_detect_ai(text, format)

Detect AI-generated text. Scores any text for AI-authorship likelihood and returns an overall verdict (AI / human / mixed) with confidence, the AI/human/AI-assisted fractions, and a segment-by-segment breakdown showing exactly which parts read as AI-written - including per-segment humanizer flags (AI output run through paraphrasing/'humanizer' tools). Use it to verify whether content (comments, articles, profiles) is AI-generated, or to check text before publishing to see which segments would trip AI detectors - revise the flagged segments and re-check. Cost scales with text length: $0.06 per 100 words, rounded up, minimum $0.06. Max input 20,000 characters.

입력 스키마

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "minLength": 50,
      "description": "Text to analyze, plain text, 50+ characters, max 20,000. Detection reliability improves with length; very short texts return lower-confidence verdicts."
    },
    "format": {
      "default": "text",
      "description": "'text' (default): compact human-readable report. 'json': structured data incl. per-segment text, scores, and humanizer flags.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "text"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_telegram_search(query, kind, format)

Search Telegram: discovers public channels by name/topic (directory lookup) and finds indexed public post/channel pages (semantic web index scoped to t.me). Telegram has no global full-text search, so treat results as discovery: find the right channel here, then use glim_telegram_get(ref=<handle>) for its live posts or glim_telegram_get(ref, query=...) to search within that channel's full history.

입력 스키마

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Search query (topic, channel name, keyword)"
    },
    "kind": {
      "default": "all",
      "description": "'channels': channel directory lookup. 'posts': indexed t.me post pages. 'all' (default): both.",
      "type": "string",
      "enum": [
        "all",
        "channels",
        "posts"
      ]
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "query"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢glim_telegram_get(ref, query, before, after, limit, ...)

Fetch a public Telegram channel or post - no account or API key involved. Channel refs (@handle, handle, t.me URL) return channel info + recent posts newest-first with views, reactions, media, polls, and link previews; pass query to search within the channel's full history, and page older posts with before=<next_cursor>. Post refs (t.me/<channel>/<id>) return that post plus its most recent discussion comments. Media URLs are Telegram CDN links that expire within hours - fetch promptly, never store. Only channels with a public web preview work (most public channels); private channels and groups are not accessible.

입력 스키마

{
  "type": "object",
  "properties": {
    "ref": {
      "type": "string",
      "description": "Public channel (@handle, handle, or t.me/<channel> URL) or post (t.me/<channel>/<id> or '<channel>/<id>')"
    },
    "query": {
      "description": "Search within the channel's full history (channel refs only)",
      "type": "string"
    },
    "before": {
      "description": "Return posts older than this message id (from next_cursor)",
      "type": "string"
    },
    "after": {
      "description": "Return posts newer than this message id",
      "type": "string"
    },
    "limit": {
      "default": 20,
      "description": "Max posts for channel refs (1-100)",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    },
    "include_comments": {
      "default": true,
      "description": "Post refs: include discussion comments (Telegram serves a small window of the most recent; walk older ones via comment=<oldest returned id>)",
      "type": "boolean"
    },
    "comment": {
      "description": "Post refs: center the comment window on this comment id",
      "type": "string"
    },
    "format": {
      "default": "text",
      "description": "Output format. 'text' (default): compact human-readable view, fewer tokens. 'json': full structured data for machine parsing.",
      "type": "string",
      "enum": [
        "text",
        "json"
      ]
    }
  },
  "required": [
    "ref"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

권장 프롬프트

search_research
Search for information about [topic] using glim.sh
예상 도구: glim_twitter_search
find_specific
Find [specific item] using glim.sh
예상 도구: glim_twitter_search
retrieve_data
Get details about [item] from glim.sh
예상 도구: glim_twitter_get
fetch_info
Fetch [information type] using glim.sh
예상 도구: glim_twitter_get
research_workflow
Search for [topic], then get detailed information about the top results using glim.sh
예상 도구: glim_twitter_searchglim_twitter_get

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