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idea-reality-mcp
We search. They guess.
The only idea validator that searches real data. 5 sources. Quantified signal. Zero hallucination.
The problem
Every developer has wasted days building something that already exists with 5,000 stars on GitHub.
You ask ChatGPT: "Is there already a tool that does X?"
ChatGPT says: "That's a great idea! There are some similar tools, but you can definitely build something better!"
That's not validation. That's cheerleading.
What we do instead
You: "AI code review tool"
idea-reality-mcp:
├── reality_signal: 90/100
├── GitHub repos: 847
├── Top competitor: reviewdog (9,094 ⭐)
├── npm packages: 56
├── HN discussions: 254
└── Verdict: HIGH — consider pivoting to a niche
One gives you encouragement. The other gives you facts.
Which one do you trust your next 3 months on?
Try it now (30 seconds)
uvx idea-reality-mcp
Or try it in your browser — no install required.
Why not just ask ChatGPT?
| idea-reality-mcp | ChatGPT / ValidatorAI / IdeaProof | |
|---|---|---|
| Data source | GitHub + HN + npm + PyPI + Product Hunt (real-time) | LLM generation (no real source searched) |
| Output | Score 0-100 + real projects with star counts | Text opinion ("Sounds promising!") |
| Verifiable | Every number has a source | Not verifiable |
| Integration | MCP / CLI / API / Web | Web-only |
| Price | Free, open-source, forever | Free trial → paywall |
| Audience | Developers (before writing code) | Non-technical founders (before writing pitch decks) |
TL;DR — We search 5 real databases. They generate opinions.
New: AI-powered search intelligence
Claude Haiku 4.5 now generates optimal search queries from your idea description — in any language — with automatic fallback to our battle-tested dictionary pipeline.
| Before | Now | |
|---|---|---|
| English ideas | ✅ Good | ✅ Good |
| Chinese / non-English ideas | ⚠️ Dictionary lookup (150+ terms) | ✅ Native understanding |
| Ambiguous descriptions | ⚠️ Keyword matching | ✅ Semantic extraction |
| Reliability | 100% (no external API) | 100% (graceful fallback to dictionary) |
The LLM understands your idea. The dictionary is your safety net. You always get results.
Make your AI agent check automatically
Add this to your .claude/instructions.md or CLAUDE.md:
Before building any new tool, feature, or project,
always run idea_check first to verify the idea hasn't been built already.
This is the highest-ROI setup. Your AI agent will validate ideas before writing a single line of code. Install once, protect every project.
More templates: Claude Code · Cursor · Windsurf · Copilot — copy-paste snippets for every AI coding tool.
Install (5 minutes)
Claude Desktop
Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"idea-reality": {
"command": "uvx",
"args": ["idea-reality-mcp"]
}
}
}
Cursor
Paste into .cursor/mcp.json in your project root:
{
"mcpServers": {
"idea-reality": {
"command": "uvx",
"args": ["idea-reality-mcp"]
}
}
}
Claude Code (CLI)
claude mcp add idea-reality -- uvx idea-reality-mcp
Smithery (Remote)
npx -y @smithery/cli install idea-reality-mcp --client claude
Optional: Environment variables
export GITHUB_TOKEN=ghp_... # Higher GitHub API rate limits
export PRODUCTHUNT_TOKEN=your_... # Enable Product Hunt (deep mode)
Usage
"I have a side project idea — should I build it?"
Tell your AI agent:
Before I start building, check if this already exists:
a CLI tool that converts Figma designs to React components
The agent calls idea_check and returns: reality_signal, top competitors, and pivot suggestions.
"Find competitors and alternatives"
idea_check("open source feature flag service", depth="deep")
Deep mode scans all 5 sources in parallel — GitHub repos, HN discussions, npm packages, PyPI packages, and Product Hunt — and returns ranked results.
"Build-or-buy sanity check before a sprint"
We're about to spend 2 weeks building an internal error tracking tool.
Run a reality check first.
If the signal comes back at 85+ with mature open-source alternatives, you just saved your team 2 weeks.
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 5 sources in parallel |
Output: reality_signal (0-100), duplicate_likelihood, evidence[], top_similars[], pivot_hints[], meta{}
{
"reality_signal": 72,
"duplicate_likelihood": "high",
"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}
],
"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...",
"Consider building an integration or plugin..."
],
"meta": {
"sources_used": ["github", "hackernews", "npm", "pypi", "producthunt"],
"keyword_source": "llm",
"depth": "deep",
"version": "0.3.2"
}
}
Scoring weights
| Mode | GitHub repos | GitHub stars | HN | npm | PyPI | Product Hunt |
|---|---|---|---|---|---|---|
| Quick | 60% | 20% | 20% | — | — | — |
| Deep | 25% | 10% | 15% | 20% | 15% | 15% |
If Product Hunt is unavailable (no token), its weight is redistributed automatically.
CI: Auto-check on Pull Requests
Add .github/workflows/idea-check.yml to run reality checks when PRs propose new features:
name: Idea Reality Check
on:
pull_request:
paths: ['docs/proposals/**', 'RFC/**']
jobs:
check:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- run: pip install idea-reality-mcp httpx
- name: Run idea check
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
python -c "
import asyncio, json
from idea_reality_mcp.sources.github import search_github_repos
from idea_reality_mcp.sources.hn import search_hn
from idea_reality_mcp.scoring.engine import compute_signal, extract_keywords
async def main():
idea = open('docs/proposals/latest.md').read()[:500]
kw = extract_keywords(idea)
gh = await search_github_repos(kw)
hn = await search_hn(kw)
report = compute_signal(gh, hn)
print(json.dumps(report, indent=2))
asyncio.run(main())
"
- name: Comment on PR
if: always()
uses: actions/github-script@v7
with:
script: |
github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: '## Idea Reality Check\nSee workflow run for full report.'
})
Roadmap
- v0.1 — GitHub + HN search, basic scoring
- v0.2 — Deep mode (npm, PyPI, Product Hunt), improved keyword extraction
- v0.3 — 3-stage keyword pipeline, 150+ Chinese term mappings, synonym expansion, LLM-powered search (Render API)
- v0.4 — Trend detection and timing analysis
- v1.0 — Idea Memory Dataset (opt-in anonymous logging)
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
Contact
Built by Mnemox AI · [email protected]