MCP
Stop drowning your agents in web data.
Same answer. 30x less noise.
Set up Stripe metered billing for my Next.js project
I'll research how to implement Stripe metered billing in Next.js...
"stripe metered billing nextjs setup"
stripe.com/docs/billing/subscriptions/usage-based
nextjs.org/docs/app/api-routes
stackoverflow.com/questions/stripe-metered...
I need more details on the usage records API...
"stripe usage records API create node"
stripe.com/docs/api/usage_records/create
research $0.01 + context $0.35 · Opus 4.6, 5 cached turns
With webrefSet up Stripe metered billing for my Next.js project
I'll research how to implement Stripe metered billing in Next.js...
webref+1.4k"How to implement Stripe metered billing in Next.js with usage-based pricing"
Stripe metered billing charges customers based on actual usage during a billing period. In Next.js, create an API route at /api/webhooks/stripe, configure a metered price in your dashboard, then report usage with stripe.subscriptionItems.createUsageRecord()...
I have everything I need. Let me implement the billing integration...
research $0.08 + context $0.01 · Opus 4.6, 5 cached turns
Deep research in under 20 seconds
Every query hits the live web — not a pre-built index.
Always fresh
Every query searches and reads the live web. Not an index from last week. Not a cached snapshot. The actual web, right now.
Deep, not shallow
Multiple search strategies fan out in parallel, gather evidence from across the web, then cross-reference and deduplicate into one cohesive answer.
sources analyzed per query
Evidence, not summaries
Your agent sees why each claim is true — not just the conclusion.
What your agent actually gets
Click a query and watch it work.
Fits into your stack
Connect webref to any AI agent with one snippet — or call the API directly.
Common questions
Isn't this just summarization?
No. Summarization loses information. webref restructures it. Search results often repeat the same facts across multiple sources with slightly different wording — we merge that into one cohesive document. The same technical details, just without the redundancy. Nothing useful gets cut.
Why not use cheaper tools?
A lower per-call price can look attractive — but the real cost is what happens after. Noisy output fills your agent's context, and by query #5 it's forgetting your original instructions. webref outputs are optimized for LLMs: your agent stays sharp even after dozens of queries.
How do I verify accuracy?
Source links are embedded directly in the text as markdown. Your agent can follow any link to read the full page if it needs more depth. We're not just giving surface-level answers — we're giving your agent a clear path to dig deeper.
Is my data private?
By default, research history is saved in your account so you can review activity and debug workflows. You can enable Privacy Mode from the usage dashboard to stop saving detailed history while keeping aggregate usage counts. Research queries are processed by webref and our infrastructure providers to deliver results — we do not use your queries to train models. API keys are encrypted at rest.
Have more questions? Read the docs