memecub: memes for writing skill

memecub: memes for writing

memecub covers trending memes: Chinese 表情包 / 斗图 (熊猫头, 奶龙, 蘑菇头, 金馆长, 吗喽…), English reaction memes and templates (Drake, This Is Fine, Doge…), plus openly licensed emoji and art.

• Memes collected from the web: license.commercial_use: false.
• Openly licensed images: license.commercial_use: true, with attribution (a ready credit line) when license.attribution_required is true.

Each result has a markdown field that already contains the credit line when one is required.

How to call it

Everything goes through one HTTPS endpoint; curl is enough. No key is needed to try it (20 searches a day per IP). With a key (MEMECUB_API_KEY) each search costs 1 credit from the user's balance (a free account gets 1,000 credits a month) and also covers their private library. The user can get a key with npx memecub login --print or at https://memecub.com/dashboard?tab=keys:

curl -sG https://memecub.com/api/v1/search \
  --data-urlencode "q=无语" -d limit=8 -d min_size=150 \
  ${MEMECUB_API_KEY:+-H "Authorization: Bearer $MEMECUB_API_KEY"}

The response is JSON: {"data": [{id, title, url, width, height, kind, license: {commercial_use, attribution_required, …}, attribution, markdown}, …], "total": …}.

Query parameters:

Parameter	Use
q	1–3 words describing the reaction or character
limit	up to 50
min_size=150	skip images too small for an article
kind=meme / kind=gif	only memes / only animated memes (when emoji or photos crowd the results)
commercial=1	only images cleared for commercial use
no_credit=1	only commercially usable images that need no credit line
private=1	only the user's own uploads (needs a key)
profanity=1	also return memes whose captions contain swearing (hidden by default; only if the user asks)

If a memecub MCP server is connected, its search_memes tool takes the same options and you can use it instead of curl.

Placing memes into an article

Do the reading yourself; only call memecub for search. This keeps cost low and gives better picks.

1. Read the whole piece. Note its language, tone, audience, and whether it is commercial (ads, sponsored posts, client work).
2. Pick the spots. Default to one image per 400–600 words (Chinese: per 600–1000 characters), at most one per section, never more than the user asked for. Good spots: a punchline, a surprise or reveal, a pain point the reader recognizes, a win, an ironic aside. Skip the title, the first sentence, code blocks, tables and anything solemn.
3. Describe each spot as a reaction, not a topic. Search for what the reader should feel. Chinese 表情包 searches work best as short 2–4 character phrases: 无语, 裂开, 震惊, 摸鱼, 打工人, 崩溃, 感动哭了. English: facepalm, mind blown, this is fine, side eye. For a named character (熊猫头, 奶龙, Drake) or the user's own mascot, search the name too.
4. Search in the article's language first, 2–3 phrasings per spot, with min_size=150. Chinese articles get Chinese 表情包 from Chinese queries; English queries mostly return English memes and emoji, so use them only as a fallback. For commercial pieces add commercial=1 if the user wants to stay safe.
5. Choose. Prefer, in order: matches the reaction precisely; the caption (title) fits the sentence; visual variety across the article (don't use the same character twice in a row). Never reuse an image in one article.
6. Insert each image on its own line right after the paragraph it reacts to, with a blank line before and after, using the result's markdown field unchanged. It already includes the credit line when the license requires one; do not strip it.
7. Report back with a short list: where each image went, which image, and whether it is cleared for commercial use. Mention any spot you skipped because nothing fit well. Do not invent images or URLs.

One-shot alternative

If the user has a key and just wants it done server-side:

curl -s -X POST https://memecub.com/api/v1/match \
  -H "Authorization: Bearer $MEMECUB_API_KEY" -H "Content-Type: application/json" \
  -d '{"text": "<the article, JSON-escaped>", "count": 4, "commercial": false}'

The response has data.markdown (the article with memes inserted) and data.slots (each spot, the chosen meme, alternatives, and placed: false if the sentence could not be found). It costs 10 credits per article (failed runs are refunded). Doing the reading yourself and calling search per spot costs 1 credit each, so prefer that.

Finding a single meme

For "find me a meme for X": search 2–3 phrasings, show the top 3–5 as Markdown images with whether each is cleared for commercial use, and let the user choose.

Rules

• Only use images returned by memecub. Never hotlink or suggest images from elsewhere as "free to use".
• Keep credit lines whenever attribution_required is true.
• If the user says the piece is commercial and you used any commercial_use: false image, say so once in your report and offer commercial=1 alternatives.
• Images marked private: true belong to the user's private library: the user declared they have rights to them. Remind the user once if such an image's declared license is non-commercial (e.g. cc-by-nc-sa) and the article looks commercial.
• If results are thin, say so and try other phrasings; memecub fetches more images for that query in the background, so retrying in a minute can help.
• On HTTP 429 without a key, the keyless daily limit is used up: tell the user to run npx memecub login --print (or create a key at https://memecub.com/dashboard?tab=keys) and set MEMECUB_API_KEY. On HTTP 402 the user's credits ran out: point them to https://memecub.com/pricing. Do not retry in a loop.