x-post-to-json

Turn any X (Twitter) post into JSON, a PDF document, a PNG card, Markdown, or a Slack/Discord post — with no API key and no login.

Zero npm dependencies. Works on Node 18+ (uses built-in fetch). PDF/PNG rendering uses your local headless Google Chrome.

node scripts/fetch-tweet.mjs "https://x.com/jack/status/20"

Why

X degrades its own content outside the platform (login walls, broken previews, deleted tweets vanish). This toolkit extracts a tweet's data through X's public syndication endpoint (the same one Vercel's react-tweet uses) and enriches it via the public GraphQL endpoint with a guest token — recovering full long-form text and complete metrics — then renders it however you need.

Outputs

All accept a tweet URL (x.com / twitter.com, with ?query//photo/1) or a bare tweet ID, and one or more inputs (batch).

Common flags

• --full — always enrich via GraphQL (full metrics even for short tweets)

• --no-enrich — pure no-auth syndication only (fastest)

• -o <path> — output file (PDF/PNG/MD)

What it extracts

Text (including full long-form), author (name, handle, avatar, verified_type), timestamp, metrics (likes / reposts / replies / quotes / bookmarks / views), media (photos + video/GIF with poster & link), links, hashtags, mentions, and quoted/reply info. Deleted / protected / age-gated / suspended tweets return a clean error.

MCP server

mcp-server.mjs exposes everything as MCP tools so any MCP client (Claude Desktop, Claude Code, Cursor, Cline, …) can call them directly. Zero dependencies (JSON-RPC over stdio). tweet_to_png_card returns the rendered image inline.

Claude Code:

claude mcp add x-post -- node "$(pwd)/mcp-server.mjs"

Claude Desktop / Cursor / Cline (claude_desktop_config.json):

{ "mcpServers": {
  "x-post": { "command": "node", "args": ["/absolute/path/to/x-post-to-json/mcp-server.mjs"] }
} }

Tools: tweet_to_json, analyze_tweet, unroll_thread, tweet_to_markdown, tweet_to_png_card, tweet_to_pdf, post_tweet_to_chat.

analyze_tweet — fact-check / explain

Turns the extractor into an analyst. The tool fetches the tweet and returns a scaffold — heuristic signals (percentages, stats/causal/sensational language, named entities, links), candidate claims, suggested search queries, author credibility, and a rubric. The host AI then runs web searches and produces a verdict card (claim → supported / misleading / false / unverifiable, the mechanism of any error, the actual evidence, and source reliability). No LLM or API key lives in this repo — the reasoning is done by whatever AI calls the tool.

Architecture

lib/tweet.mjs              shared fetch + normalize engine (fetchTweet)
lib/render.mjs             shared render helpers (esc, richText, fmt*, embedAssets)
scripts/fetch-tweet.mjs    JSON
scripts/tweet-to-pdf.mjs   PDF document
scripts/tweet-to-png.mjs   PNG card
scripts/tweet-to-md.mjs    Markdown
scripts/tweet-to-chat.mjs  Slack/Discord
scripts/analyze-tweet.mjs  fact-check scaffold
scripts/unroll-thread.mjs  thread unroll (backward walk)
mcp-server.mjs             MCP wrapper

To add an output format, import the engine + lib/render.mjs and reuse the normalized object — don't re-implement fetching.

Caveats

• Uses X's undocumented public endpoints. They can change; GraphQL enrichment is best-effort and degrades gracefully (falls back to the syndication preview, flags truncated). If enrichment stops working, the GQL_QUERY_ID in lib/tweet.mjs likely rotated and needs updating.

• Public tweets only. Respect X's Terms of Service and applicable laws for your use case.

• PDF/PNG require Google Chrome installed (path is /Applications/Google Chrome.app/... on macOS — adjust in the scripts for other OSes).

License

MIT © itsbigdill