Searches GitHub repositories and star counts to identify existing open-source projects and assess competition for a given idea.
Scans the npm registry for existing packages and tools to determine if a JavaScript-related idea has already been implemented.
Searches for launched products on Product Hunt to identify existing competitors and market entries.
Scans the Python Package Index to find existing Python libraries and tools matching a project description.
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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 nicheOne 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-mcpOr 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-mcpSmithery (Remote)
npx -y @smithery/cli install idea-reality-mcp --client claudeOptional: 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 componentsThe 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 |
| string | yes | Natural-language description of idea |
|
| no |
|
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 · dev@mnemox.ai