The Problem
AI agents are getting good at business intelligence tasks. But they still can't access most domain-specific data — it's locked in PDFs, behind paywalls, or formatted for humans.
I built a sports sponsorship intelligence API that's natively accessible to AI agents via Model Context Protocol (MCP).
What It Does
Query: GET /api/match-score?club=everton&brand=Revolut
Response: Structured JSON with:
- Match score (1-100)
- Reasoning
- Comparable deals
- Risk factors
- Suggested deal terms
Why MCP?
MCP lets AI agents discover and use your API without custom integration. Any MCP-compatible agent finds the endpoint at:
https://sportsignal.agency/.well-known/mcp.json
The Business Case
£83.9M in Premier League sponsorship revenue is changing hands due to the UK gambling ad ban. 11 clubs need new sponsors. I built the scoring layer for this market.
Scoring Algorithm
- Fan base reach: 30%
- Digital presence: 20%
- Category fit: 35%
- Sponsorship gap urgency: 15%
Try It
Free tier: all 11 gambling-affected PL clubs → sportsignal.agency/match-score
Feedback welcome — especially on MCP implementation patterns.
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