I wasted 6 hours building something that already had 847 GitHub repos

Last month I told Claude: "Build me an AI-powered food recommendation engine." It did. Beautifully. Clean code, tests passing, README done. Then I searched GitHub. 847 repos. Twelve of them had over 100 stars. Some were updated that same week. I had just mass-produced another clone. Every AI coding tool in 2026 makes you build faster. Cursor, Claude Code, Copilot — they're all racing to write code at the speed of thought. But none of them ask the one question that matters: Should you build this at all? Idea Reality MCP is an MCP server — not a website, not a dashboard, not another SaaS validator. It's a tool your AI agent calls before it starts building. Install: uvx idea-reality-mcp

Add to Claude Desktop config: { "mcpServers": { "idea-reality": { "command": "uvx", "args": ["idea-reality-mcp"] } } }

Then just tell Claude: "Check if this idea already exists before we build it." { "reality_signal": 82, "duplicate_likelihood": "high", "evidence": [ {"source": "github", "type": "repo_count", "count": 847}, {"source": "github", "type": "high_star_repos", "count": 12}, {"source": "hn", "type": "mention_count", "count": 34} ], "top_similars": [ {"name": "food-rec-ai", "stars": 2340, "updated": "2026-02-18"} ], "pivot_hints": [ "Space is saturated. Consider vertical-specific targeting.", "Most existing tools are generic — niche wins." ] }

An 82 means: stop. Research first. Pivot or differentiate. A 15 means: green light. The space is open. Idea validators already exist as websites — IdeaProof, ValidatorAI, DimeADozen, FounderPal. There are dozens. But they all require you to leave your workflow, open a browser, type your idea, wait for a report, then go back to coding. That's the wrong architecture. The check should happen inside the moment you decide to build. MCP makes this possible. Your AI agent calls idea_check() the same way it ca