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idea-reality-mcp

Your AI agent checks before it builds. Automatically.

The only MCP tool that searches 5 real databases before your agent writes a single line of code. No manual search. No forgotten step. Just facts.

<p align="center"> <a href="https://mnemox.ai/check"><strong>👉 Try it in your browser — no install</strong></a> </p>

What it does

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 number. Five real sources. Your agent decides what to do next.

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.

"Why not just Google it?"

This is the most common question we get. Here's the honest answer:

Google works — if you remember to use it. The problem isn't search quality. The problem is that your AI agent never Googles anything before it starts building.

idea-reality-mcp runs inside your agent. It triggers automatically. The search happens whether you remember or not.

	Google	ChatGPT / SaaS validators	idea-reality-mcp
Who runs it	You, manually	You, manually	Your agent, automatically
Input	You craft the query	Natural language	Natural language
Output	10 blue links — you interpret	"Sounds promising!"	Score 0-100 + evidence + competitors
Sources	Web pages	None (LLM generation)	GitHub + HN + npm + PyPI + PH
Cross-platform	Search each site separately	N/A	5 sources in parallel, one call
Workflow	Copy-paste between tabs	Separate app	MCP / CLI / API / CI
Verifiable	Yes (manual)	No	Yes (every number has a source)
Price	Free	Free trial → paywall	Free, open-source, forever

TL;DR — You don't use it. Your agent does. That's the point.

Try it (30 seconds)

uvx idea-reality-mcp

Or try it in your browser — no install, instant results.

Install

Claude Code (CLI) — fastest

claude mcp add idea-reality -- uvx idea-reality-mcp

Claude Desktop / Cursor

Paste into your MCP config (claude_desktop_config.json or .cursor/mcp.json):

{
  "mcpServers": {
    "idea-reality": {
      "command": "uvx",
      "args": ["idea-reality-mcp"]
    }
  }
}

<details> <summary>Config file locations</summary>

• Claude Desktop (macOS): ~/Library/Application Support/Claude/claude_desktop_config.json
• Claude Desktop (Windows): %APPDATA%\Claude\claude_desktop_config.json
• Cursor: .cursor/mcp.json in project root

</details>

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)

Optional: Agent auto-trigger

The MCP tool description already tells your agent what idea_check does. To make it run proactively (before every new project), 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.

See templates/ for all platforms.

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.

New: AI-powered search intelligence

Claude Haiku 4.5 generates optimal search queries from your idea description — in any language — with automatic fallback to our 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.

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{}

<details> <summary>Full output example</summary>

{
  "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": "0.4.0"
  }
}

</details>

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

Use idea-check-action to validate new 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 }}

Roadmap

• [x] v0.1 — GitHub + HN search, basic scoring
• [x] v0.2 — Deep mode (npm, PyPI, Product Hunt), improved keyword extraction
• [x] v0.3 — 3-stage keyword pipeline, 150+ Chinese term mappings, synonym expansion, LLM-powered search (Render API)
• [x] v0.4 — Email gate, Score History, Agent Templates, GitHub Action
• [ ] v0.5 — Temporal signals (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:

1. Open an issue with your idea text and the output
2. We'll improve the keyword extraction for your domain

License

MIT — see LICENSE

Contact

Built by Mnemox AI · dev@mnemox.ai