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SE Ranking•Apr 2025 - Present•3 min read

MCP Driving 30% of Signups

Senior Technical Product Manager - API

First to ship MCP. Iterated from local to remote. Now 30% of signups

APIAI/ML0-to-1GTMPMF

TL;DR

First to ship Model Context Protocol (MCP) in the SEO/search space. Iterated from local/subscription (poor retention) to remote/pay-as-you-go (signups skyrocketed). Now accounts for 30% of company signups—SEO professionals querying data via ChatGPT, Claude, and Gemini.

Context

AI agents needed easy ways to access SEO data. Model Context Protocol (MCP) was emerging as the standard for connecting AI assistants to external data sources. Being first to market could capture a new segment.

Problem

  • AI agents couldn't easily access SEO data
  • Technical barrier was high for non-developers
  • Traditional API required coding knowledge
  • SEO professionals wanted natural language access to data

What I Did

V1: Local Setup + Subscription

  • Shipped MCP integration running locally
  • Required technical setup (Node.js, configuration files)
  • Subscription-based pricing model

Result: Poor retention. Setup was too technical, and subscription created friction for occasional users.

V2: Remote + Pay-as-You-Go

  • Pivoted to remote-hosted MCP server
  • Pay-as-you-go pricing (no subscription required)
  • One-click setup in Claude, ChatGPT, and Gemini

Result: Signups skyrocketed.

Key Decisions

Bet Early on Emerging Protocol

Committed to MCP before it was widely adopted. Being first established us as the go-to SEO data source for AI assistants.

Remove Friction at Every Step

V1 failed because of friction. V2 succeeded by eliminating setup complexity and subscription commitment.

Target Non-Developers

Realized the market wasn't AI developers (who use the API directly) but SEO professionals who wanted natural language access.

Technical Details

  • MCP Server: Remote-hosted server handling authentication and rate limiting
  • Pay-as-You-Go Metering: Usage-based billing integrated with existing payment infrastructure
  • Multi-Platform Support: Compatible with Claude, ChatGPT, and Gemini
  • Natural Language Interface: Optimized prompts and responses for conversational queries

Results

30%
Of Company Signups
First
To Ship MCP in Space
3
AI Platforms Supported
  • SEO professionals querying data via natural language on ChatGPT, Claude, and Gemini
  • Opened AI agent and no-code markets (n8n, Make.com)
  • Created new acquisition channel independent of traditional marketing

Lessons Learned

  1. Iteration beats perfection: V1 failed, but fast iteration to V2 captured the market. Shipping early let us learn.
  2. Friction kills products: The difference between V1 and V2 was entirely about reducing friction—same core technology.
  3. First-mover advantage is real: Being first to ship MCP in our space established us as the default choice.
  4. Find the real user: We thought we were building for developers but found product-market fit with SEO professionals.