glim.sh

Give your agent live data from Twitter, Reddit, the web, GitHub, Amazon, YouTube and public Telegram channels, plus AI-text detection.

CommunityOnlineNo sign-inRU / CISFreeRead-only

What it can do

  • Glim Twitter Search: 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://sear
  • Glim Twitter Get: 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
  • Glim Reddit Search: 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 b

What data it sees

Do you need an account

No: the server works without sign-in

Give your agent live data from Twitter, Reddit, the web, GitHub, Amazon, YouTube and public Telegram channels, plus AI-text detection. No API keys, no scraping stack.

How to connect

How to connect glim.sh to Claude

The server address to paste into Claude settings:

https://glim--glim.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect glim.sh to ChatGPT

The server address to paste into ChatGPT settings:

https://glim--glim.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect glim.sh to Cursor

The server address to paste into Cursor settings:

https://glim--glim.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (14)

Raw names from tools/list. Only developers need these.

glim_twitter_searchSearch 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.
glim_twitter_getFetch 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.
glim_reddit_searchSearch 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.
glim_reddit_getFetch a Reddit post, subreddit, or user by ref. Posts return comments; subreddits and users return profile metadata plus recent activity.
glim_web_searchSemantic 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.
glim_web_fetchFetch 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.
glim_github_searchSearch GitHub repositories, conversations (issues+PRs), 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. 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:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos). Returns compact text by default; pass format='json' for full structured data.
glim_github_getFetch 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, /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).
glim_amazon_searchPass 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.
glim_amazon_getFetch 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.
glim_youtube_getFetch 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.
glim_detect_aiDetect 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. 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. tier='premium' uses the most accurate detection class, additionally flags humanized text (AI output run through paraphrasing/'humanizer' tools), and is substantially more robust to evasion, at ~10x the price of 'standard'. Cost scales with text length: ~$0.06 per 1,000 words standard, ~$0.60 premium; minimum $0.06. Texts under ~100 words are automatically analyzed with the premium class at the standard price.
glim_telegram_searchSearch 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.
glim_telegram_getFetch 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.