Seed
A topic expands into thousands of real queries via DataForSEO Labs.
OBSERVATORY · CURIOSITYGRAPH
CuriosityGraph shows you every question your market is asking about any topic — ranked by real search demand, organized the way people actually think, and handed to your content team or your AI agent. Stop guessing what your customers want. Read it.
Your content calendar and your roadmap come from a brainstorm, not from what your audience actually searched for this month. You ship the thing you think matters and hope you were right.
AnswerThePublic and the rest hand you hundreds of ungrouped phrases. You cannot tell which are the same question worded ten ways, which have real demand behind them, or which actually change a decision.
Real curiosity branches — how-to, does-it-work, is-it-worth-it, this-versus-that, what-goes-wrong. You need the map of how a customer reasons through your category. No one draws it for you.
The most honest focus group in history is running right now. It is called search — billions of people typing exactly what they want, unprompted, at the moment they want it. You just have not been able to read it.
Point CuriosityGraph at a topic. It reads thousands of real searches, merges the ones that mean the same thing, ranks them by summed monthly volume, and labels how each is asked. Here is an actual result from the live corpus — sourdough bread:
The top line — how to make sourdough bread starter — is 940,300 searches a month, 25 different phrasings collapsed into one. The lines below it are the objections and follow-ups people also ask — the doubts that decide whether they buy your product or trust your guide. That is not a keyword list. It is your customer's mind, ranked.
Every question above is real, pulled live from the corpus. We never invent data — when we don't have it, we say so.
Fill the calendar with demand-backed briefs. Build topic clusters that own a category. Every article maps to real questions with real volume — and comes with its H2/H3 skeleton and FAQ already outlined.
See what your market wants to know before they buy, and the objections that stop them. Write docs, FAQs, and positioning that answer real questions — and quietly cut your support load.
Question intelligence inside your pipeline. Call research_topic from Claude, Cursor, or n8n and get structured, ranked questions back — at scale, for every client, without a human in the loop.
Instant command of a niche. Understand what your audience is asking and produce content like you have a research team behind you — because now you do.
Real data, eight steps, nothing invented. Every question is backed by real search volume; semantically identical queries are merged by meaning, not string-match; each cluster is verified before it earns its place.
A topic expands into thousands of real queries via DataForSEO Labs.
Interrogatives and comparisons become questions; the remainder is the tag pool.
People-Also-Ask questions harvested from the live SERP, one level deep.
Queries embedded with bge-m3 and merged by semantic identity.
A model confirms each cluster and names its canonical question.
Real keywords attach to clusters by cosine similarity, weighted by volume.
Clusters ranked by summed real search volume; PAA presence breaks ties.
Themes, trees, and article briefs — cached as a compounding question graph.
CuriosityGraph is agent-first. Call it over MCP from Claude, Cursor, or n8n; hit the REST API from any language; or run the CLI. Structured, ranked question intelligence flows straight into your pipeline — first agent call in under two minutes.
Connect your agent in under two minutes.
mcp.curiositygraph.com
tools: research_topic · expand_question
get_tree · get_tags · generate_briefOpenAPI-first. Async jobs, polling, HMAC webhooks.
POST /v1/jobs { topic, depth }
GET /v1/jobs/{id}
GET /v1/jobs/{id}/resultRead the docs →Prints your key, runs a sample job.
npx curiositygraph "solar panels"
This is the age of agentic code. Point Claude Code, Cursor, or an n8n prompt node at CuriosityGraph and it pulls real customer questions, then writes the content around them. Paste one of these and go.
Use the CuriosityGraph MCP to research "cast iron skillet care". Take the 8 highest-volume questions, write a guide that answers each as an H2 — highest demand first — and add an FAQ from the questions people also ask. Note the monthly volume per section.
Call research_topic on "sourdough bread" via CuriosityGraph. Cluster the questions into 10 article ideas, rank them by summed search volume, and lay out a 4-week calendar — one pillar plus supporting posts — with the target question and demand for each.
Research "electric vs gas water heater" with CuriosityGraph and pull the comparison and objection questions. Generate a React FAQ component that answers the top 12 — each with a short, accurate answer that pre-empts the doubt.
Every Monday: research_topic on our 5 product categories, flag any question that newly crossed 1,000 searches/mo, generate_brief for each, and open a draft in the CMS — no human in the loop.
Connect once — mcp.curiositygraph.com — or hit the REST API from any language. Every free account ships with a key.
Every job you run enriches a shared graph of questions, volumes, and relations. Because results cache, popular topics cost pennies and answer in seconds — you are building an asset, not renting a dashboard.
Prepaid credits, no subscription to forget about. A quick job is 1 credit, standard 4, deep 10 — and warm topics you have already charted are nearly free.
START HERE