Your dev workflow, for your website

Your website is your product. Ship it like one.

You already know how to ship software: observe, spec, build, verify, iterate. Rampify brings that same discipline to your website’s search and AI visibility, the part of your product the world actually sees, inside the agent you already build with.

Zero install · OAuth · works in Claude Code, Cursor, VS Code, and Claude

The gap

SEO data is everywhere. Acting on it is the hard part.

There’s no shortage of SEO MCP servers. DataForSEO, Ahrefs, Semrush, SE Ranking, and the Google Search Console MCP all bring real data into your agent. But they’re read-only, and each one is a separate faucet. They tell you the title tag is too long, the schema is missing, the page is thin. Then you switch to your editor, reconcile three tools’ worth of output in your head, and do the work yourself.

The data was never the bottleneck. The synthesis and the work are. Rampify is built for both.

Same discipline

It’s the same discipline you already use

Shipping software is observe, spec, build, verify, iterate. Getting your website found is the same work in a different discipline. Rampify makes your website answer to it.

StageHow you ship softwareYour website, with Rampify
ObserveLogs, errors, metricsCrawl, Search Console, and Discovery (where you’re invisible in AI answers)
SpecPlan the changeA feature spec with affected URLs and exact instructions
BuildImplementGenerate meta, schema, and content
VerifyTests and CIRe-scan the page and validate the schema
ShipPR and deployA PR to your repo, or a publish via your CMS’s MCP
IterateMeasure, adjustRe-run Discovery, track citations, adjust

Same architecture, different discipline. Your website is the part of your product the world sees first; this is how you ship it with the rigor you already give your code.

What it is

SEO that runs where you already work

Rampify is a remote MCP server that speaks the Model Context Protocol, the open standard from Anthropic for connecting AI assistants to external tools. Connect once over OAuth, with no install and nothing to keep updated; new tools appear automatically. From inside Claude Code, Cursor, VS Code, Windsurf, or the Claude apps, your agent can:

  • Crawl and scan your site (meta, schema, content, Core Web Vitals) and pull it together with keyword data and Search Console performance
  • Generate the fix titles, descriptions, JSON-LD schema, grounded in that synthesis, not the model’s guess
  • Write it up as a spec with the affected URLs and exact change instructions
  • Ship it hand the work to your agent: a PR to your repo, or a publish through your CMS’s MCP

It doesn’t stop at analysis. It turns findings into work your agent can ship. That’s the difference.

What’s unique

Track it like you track code

No other SEO MCP does this. Rampify turns findings into feature specs with affected URLs and tasks, then links the commits that resolve them, so your marketing work has the same paper trail as your engineering.

  • create_feature_spec / create_spec_task: plan the change as a spec with tasks
  • link_commit: attribute the commit that shipped it
  • get_commit_message: generate the message, spec trailer and all

Spec it, ship it, link the commit. The same workflow you already trust, pointed at the part of your product the world actually sees.

Try these

Things to ask once you’re connected

No commands to learn. Talk to your agent the way you already do:

Crawl my site and show me which pages are invisible when buyers ask AI assistants about my category.
Research keywords for /pricing, then write the content spec.
Audit the meta and schema on my top pages, and open a PR with the fixes.
Run a Discovery sweep as my ICP buyer and turn the gaps into feature specs.

Why the fix is worth trusting

Grounded in your actual site, not the model’s guess

Any agent can edit a title tag. The question is whether it should. Rampify’s recommendations come from synthesis, not vibes:

A real crawl of your site

Rampify reads your actual pages, not a cached snapshot or assumptions, and overlays the data onto them. Your site is the source of truth.

Multiple sources, one picture

Page intelligence, keyword data, and Search Console performance are combined into one view, so a recommendation reflects what’s true across all of them.

Gaps you can’t see from inside

Discovery sends queries out as your buyer and reports where you’re invisible in AI answers and search, so you fix what costs you customers, not what’s merely untidy.

Organized as specs, built for handoff

Findings become feature specs with affected URLs and concrete instructions. The work is structured the moment it’s identified, and your agent has everything it needs to execute.

This is what turns a coding agent into a marketing agent: not a slogan, but synthesized, site-specific data plus a clean path to act on it.

See a real session

What it actually looks like

No dashboard tour. Here’s a developer working on their Next.js SaaS, in the flow of one chat. The notes call out what’s happening under the hood.

Illustrative session: the tool names are real; the example is representative. We run this same loop on rampify.dev itself.

You
I just shipped the rework of our /pricing page. How’s it doing for SEO, and would it even show up if someone asked an AI assistant to recommend a tool in our space?
Agent · Rampify connected
Give me a second to look at the live page and pull the data together.
crawl_site · get_page_intelligence · lookup_keywords · get_search_performance
Here’s the synthesis: your title is generic and there’s no Product/Offer schema, so AI engines can’t read your plans. Search Console shows impressions for “[your brand] pricing” but almost nothing for the non-branded queries that bring new buyers. And for “best tool for [your use case],” competitors get surfaced and you don’t. The page isn’t structured to be quoted by an answer engine.
What’s happeningOne question → a synthesis across a live crawl, keyword data, and Search Console. The agent didn’t guess from training data; it read your page as it is right now.
You
The AI-visibility part worries me more than the rankings. Can you dig into that?
Agent · Rampify connected
Running a Discovery check. I’ll ask the questions a buyer in your category would actually ask an assistant, and see where you land.
start_discovery · scenario sweep
You’re invisible for the buyer questions, not just the branded ones. The common thread with the on-page finding: there’s no content structured as an answer, and no schema for the engine to lift.
What’s happeningDiscovery sends queries out as your buyer and reports where you’re absent: gap-finding grounded in what real answer engines return, not a vanity score.
You
Okay. Let’s fix the pricing page at least. What do you recommend?
Agent · Rampify connected
Three changes, in priority order. I’ve written them up as a spec so the work’s organized and I can pick it straight up:
create_feature_spec · create_spec_task ×3
Spec: Make /pricing answerable for non-branded + AI-answer queries
1. Add Product + Offer JSON-LD per tier
2. Rewrite title + meta to target “[category] for [use case]” intent
3. Add an answer-shaped “Which plan is right for you?” FAQ, schema-backed
Affected URL: /pricing. Each task has the exact change. Want me to start with the schema?
What’s happeningThe recommendation becomes a spec with affected URLs and concrete instructions, not a checklist you re-explain. This is the handoff that keeps multi-step work coherent.
You
Do all three.
Agent · Rampify connected
On it.
edit app/pricing/page.tsx · add components/PricingSchema.tsx · open PR
Done. The PR is up. I added the JSON-LD as a component, updated generateMetadata for the new title/description, and added the FAQ block with matching FAQPage schema. The diff’s scoped to the pricing route; nothing else touched. Review when you’re ready.
What’s happeningRead-write, and codebase-aware: it edited the right Next.js files and opened a real PR. This is exactly where a read-only data MCP stops and hands the work back to you.
You
Merged and deployed.
Agent · Rampify connected
Re-checking the live page.
scan_page · link_commit · update_spec_task
Confirmed: the schema is valid, the new title is live, and the FAQ renders. I’ve linked the commit to the spec and closed the three tasks. I’ll re-run the Discovery check on the next sweep to see if you start surfacing for the buyer queries; that one’s a trend, not an overnight change.
What’s happeningThe loop closes itself: verify the fix shipped, attribute the commit to the spec, and the same conversation that found the problem solved it.

Four things just happened that a data-only MCP plus a generic agent can’t do together:

Synthesis: one picture from a live crawl + keywords + Search Console
Site-grounded: read your actual page, overlaid the data onto it
Spec handoff: findings organized into executable work
Ship + verify: shipped the fix and confirmed it landed

One connection

One brain for SEO. Composable with everything else.

The common setup stitches two to four MCP servers (one for keywords, one for Search Console, one for backlinks), each a stateless faucet that doesn’t know about the others. Rampify is one connection that already includes the keyword data (DataForSEO) and your Search Console performance, and the steps feed each other: the crawl and keyword data ground the spec, the spec drives the fix, the fix gets verified.

And it doesn’t lock you to a surface. Rampify is the decision layer: it works out what to change and why. Your agent is the execution layer. Point it at your repo and it opens a PR; pair it with a CMS’s MCP server (the Sanity MCP, say) and the same agent researches, specs, and publishes.

This isn’t about having more data than the dedicated providers; they’re excellent at that. It’s one coherent brain that plays well with the rest of your stack.

Where Rampify fits

Data layers read. Rampify acts.

ServerWhat it doesRead / act
DataForSEO / Ahrefs / Semrush / SE Ranking MCPKeyword, rank, backlink, and SERP dataRead-only data layer
Google Search Console MCPYour first-party search performanceRead-only; Rampify already includes it
next-devtools-mcp (Vercel)Routes, metadata, and errors from your dev serverCode-aware, read-focused
Frase MCPContent creation that publishes to its CMS integrationsActs, but closed and marketer-first
RampifyCrawls, synthesizes, and specs the fix; your agent ships itReads and acts; composable

Rampify already includes the data most of these cover: keyword search volume via DataForSEO and your Search Console performance. That’s one connection, not three, and it acts on the data instead of just handing it back.

It’s honest about scope: Rampify isn’t a backlink database or a large-scale rank tracker, so for those a dedicated vendor still has its place. It’s built for developers who control their site, not for managing content inside a single closed CMS.

Builders who ship with Rampify

MO
Mario Ottmann
Solopreneur

I always knew SEO and AEO are important but dealing with individual error files of ahrefs or the cryptic GSC warnings were such a blocker taking care of the basics. With Rampify, I finally have the tool that not just gives me data but gives me the solution to all my problems at the click of a button. For the first time, SEO and AEO are not just easy but fun to work on.

JW
Jason Wolf
Neon Deer Data Labs

Before Rampify, I was fumbling in the dark. I'd try things that seemed important, piece together scraps of data from Plausible and Search Console, but never tie any of it into a real strategy. With Rampify, we built out a real business profile, ran discovery to see where Claude was (and wasn't) recommending us, turned the gaps into actual content specs, and shipped them. For the first time, I can see how LLMs are citing our pages and act on it. For a small business owner where marketing always seems to take a back seat, that's been a game changer. Highly recommend.

Connect

Connect in three steps

  1. 1

    Add the server

    In Cursor or VS Code, one-click add. In Claude Code or Desktop, paste one command. In claude.ai, add it as a custom connector by URL.

  2. 2

    Pick your project

    The OAuth flow scopes Rampify to the project you’re working on. No API keys to manage.

  3. 3

    Start talking

    Ask your agent to crawl your site and find the gaps. The tools appear automatically.

https://www.rampify.dev/api/mcp

FAQ

Common questions

What is the Rampify MCP server?

A remote Model Context Protocol server that gives your AI coding agent SEO tools (site crawl, page scans, issue detection, meta and schema generation, keyword research, and Google Search Console access). Unlike read-only SEO MCP servers, it synthesizes what it finds and turns it into specs and fixes your agent can ship.

How is it different from the DataForSEO, Ahrefs, or Semrush MCP servers?

Those are read-only data layers: they bring SEO data into your agent. Rampify synthesizes data across a crawl of your own site plus keyword and Search Console data, then turns it into specs and changes your agent can ship. It complements a data MCP rather than replacing it.

Does it only work on Next.js or custom-coded sites?

No. Rampify is the SEO decision layer; your agent does the writing. On a custom-coded site it opens a PR to your repo. On a CMS, the agent can publish through that CMS’s own MCP server (for example, the Sanity MCP). Rampify stays surface-agnostic.

What is the best SEO MCP server for Claude Code or Cursor?

For pulling data, the dedicated data providers are strong. For acting on SEO inside your workflow, not just reading it, Rampify is built for that: it crawls and synthesizes, specs the fix with affected URLs, and your agent ships it.

Do I need to install anything?

No. It is a remote server. You connect over OAuth and start using it; new tools appear automatically with no version updates.

Do I need the Google Search Console or DataForSEO MCP servers too?

No. Rampify already retrieves your Google Search Console performance and keyword data (via DataForSEO) as built-in tools, so you don’t need separate data servers for those. For deep backlink databases or large-scale rank tracking, a dedicated vendor still has its place.

What does a typical session look like?

You ask your agent about a page or your site; it crawls and synthesizes the data, flags the gaps including where you are invisible in AI answers, writes the fix up as a spec, ships it as a pull request or a CMS publish, and verifies the change after deploy, all in one conversation.

Bring SEO into the agent you already use.

Connect once and your agent can crawl, synthesize, spec, and ship. No install, no API keys, no dashboard to babysit.

Free to connect · OAuth · works in Claude Code, Cursor, VS Code, and Claude