idea-reality-mcp
Pre-build reality check for AI agents. Scans GitHub, HN, npm, PyPI & Product Hunt — returns a 0-100 signal.
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idea-reality-mcp
Stop building what already exists.
You spend 3 weeks coding a tool. Ship it. Then find out someone already built it — with 5,000 stars.
idea_check scans GitHub, Hacker News, npm, PyPI, Product Hunt, and Stack Overflow before your agent writes a single line of code. One call. Six databases. A score instead of a guess.
What you get
You: "AI code review tool"
idea_check →
├── reality_signal: 92/100
├── trend: accelerating ↗
├── market_momentum: 73/100
├── GitHub repos: 847 (45% created in last 6 months)
├── Top competitor: reviewdog (9,094 ⭐)
├── npm packages: 56
├── HN discussions: 254 (trending up)
└── Verdict: HIGH — market is accelerating, find a niche fast
One score. Six sources. Trend detection. Your agent decides what to do next.
Try it in your browser — no install
Quick Start
1. Install and run
uvx idea-reality-mcp
2. Add to your MCP client
Claude Desktop — claude_desktop_config.json
{
"mcpServers": {
"idea-reality": {
"command": "uvx",
"args": ["idea-reality-mcp"]
}
}
}
Config location: macOS ~/Library/Application Support/Claude/claude_desktop_config.json · Windows %APPDATA%\Claude\claude_desktop_config.json
Claude Code
claude mcp add idea-reality -- uvx idea-reality-mcp
Cursor — .cursor/mcp.json
Or click the button above for one-click install.
{
"mcpServers": {
"idea-reality": {
"command": "uvx",
"args": ["idea-reality-mcp"]
}
}
}
Smithery (remote, no local install)
npx -y @smithery/cli install idea-reality-mcp --client claude
3. Use it
Tell your agent:
Before I start building, check if this already exists:
a CLI tool that converts Figma designs to React components
That's it. The agent calls idea_check and returns: reality_signal, top competitors, and pivot suggestions.
Why not just Google it?
Google works — if you remember to use it. The problem isn't search quality. It's that your AI agent never Googles anything before it starts building.
idea_check runs inside your agent. It triggers automatically. The search happens whether you remember or not.
| ChatGPT / SaaS validators | idea-reality-mcp | ||
|---|---|---|---|
| Who runs it | You, manually | You, manually | Your agent, automatically |
| Output | 10 blue links | "Sounds promising!" | Score 0-100 + evidence + competitors |
| Sources | Web pages | None (LLM generation) | GitHub + HN + npm + PyPI + PH + SO |
| Workflow | Copy-paste between tabs | Separate app | MCP / CLI / API / CI |
| Price | Free | Free trial → paywall | Free & open-source (MIT) |
Modes
| Mode | Sources | Use case |
|---|---|---|
| quick (default) | GitHub + HN | Fast sanity check, < 3 seconds |
| deep | GitHub + HN + npm + PyPI + Product Hunt + Stack Overflow | Full competitive scan |
Scoring weights
| Source | Quick | Deep |
|---|---|---|
| GitHub repos | 60% | 22% |
| GitHub stars | 20% | 9% |
| Hacker News | 20% | 14% |
| npm | — | 18% |
| PyPI | — | 13% |
| Product Hunt | — | 14% |
| Stack Overflow | — | 10% |
If Product Hunt or Stack Overflow is unavailable, their weight is redistributed automatically.
Tool schema
idea_check
| Parameter | Type | Required | Description |
|---|---|---|---|
idea_text | string | yes | Natural-language description of idea |
depth | "quick" | "deep" | no | "quick" = GitHub + HN (default). "deep" = all 6 sources |
Full output example
{
"reality_signal": 72,
"duplicate_likelihood": "high",
"trend": "accelerating",
"sub_scores": { "market_momentum": 73 },
"evidence": [
{"source": "github", "type": "repo_count", "query": "...", "count": 342},
{"source": "github", "type": "max_stars", "query": "...", "count": 15000},
{"source": "hackernews", "type": "mention_count", "query": "...", "count": 18},
{"source": "npm", "type": "package_count", "query": "...", "count": 56},
{"source": "pypi", "type": "package_count", "query": "...", "count": 23},
{"source": "producthunt", "type": "product_count", "query": "...", "count": 8},
{"source": "stackoverflow", "type": "question_count", "query": "...", "count": 120}
],
"top_similars": [
{"name": "user/repo", "url": "https://github.com/...", "stars": 15000, "description": "..."}
],
"pivot_hints": [
"High competition. Consider a niche differentiator...",
"The leading project may have gaps in..."
]
}
REST API
Not using MCP? Call it directly:
curl -X POST https://idea-reality-mcp.onrender.com/api/check \
-H "Content-Type: application/json" \
-d '{"idea_text": "AI code review tool", "depth": "quick"}'
Free. No API key required.
CI: Auto-check on Pull Requests
Use idea-check-action to validate feature proposals:
name: Idea Reality Check
on:
issues:
types: [opened]
jobs:
check:
if: contains(github.event.issue.labels.*.name, 'proposal')
runs-on: ubuntu-latest
steps:
- uses: mnemox-ai/idea-check-action@v1
with:
idea: ${{ github.event.issue.title }}
github-token: ${{ secrets.GITHUB_TOKEN }}
Optional config
export GITHUB_TOKEN=ghp_... # Higher GitHub API rate limits
export PRODUCTHUNT_TOKEN=your_... # Enable Product Hunt (deep mode)
Auto-trigger: Add one line to your CLAUDE.md, .cursorrules, or .github/copilot-instructions.md:
When starting a new project, use the idea_check MCP tool to check if similar projects already exist.
Roadmap
- v0.1 — GitHub + HN search, basic scoring
- v0.2 — Deep mode (npm, PyPI, Product Hunt), keyword extraction
- v0.3 — 3-stage keyword pipeline, Chinese term mappings, LLM-powered search
- v0.4 — Score History, Agent Templates, GitHub Action
- v0.5 — Temporal signals, trend detection, market momentum
- v1.0 — Idea Memory Dataset (opt-in anonymous logging)
Star History
Found a blind spot?
If the tool missed obvious competitors or returned irrelevant results:
- Open an issue with your idea text and the output
- We'll improve the keyword extraction for your domain
License
MIT — see LICENSE
Built by Mnemox AI · [email protected]
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