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idea-reality-mcp

Organization
mnemox-ai

Pre-build reality check for AI coding agents. Scans GitHub, HN, npm, PyPI, Product Hunt. MCP server. 290+ stars.

Publishermnemox-ai
Repositoryidea-reality-mcp
LanguagePython
Forks
88
Stars
821
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    idea-reality-mcp exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    821 stars and 88 forks from the linked repository.

English | 繁體中文

idea-reality-mcp

How to check if someone already built your app idea — automatically.

idea-reality-mcp is an MCP server that scans GitHub, npm, PyPI, Hacker News, and Stack Overflow to check if your startup idea already exists. It returns a 0–100 reality score with evidence, trend detection, and pivot suggestions — so your AI agent can decide whether to build, pivot, or kill the idea before writing any code.

When to use this: You're about to start a new project and want to know if similar tools already exist, how competitive the space is, and whether the market is growing or declining.

Project status (August 2026): Maintenance mode. The tool works, stays free & open source, and the hosted API remains up; bug reports are reviewed, but no new features are planned.

Not just checking — building it? After a reality check, open your idea as a public project on AngelRun — ship updates, climb the season, and get seen by angels.

PyPI Smithery License: MIT CI GitHub stars Downloads

How it works

  1. Describe your idea in plain English — e.g. "a CLI tool that converts Figma designs to React components"
  2. idea_check scans 5 databases in parallel (GitHub repos + stars, Hacker News discussions, npm/PyPI packages, Stack Overflow questions)
  3. Get a 0–100 reality score with trend direction (accelerating/stable/declining), top competitors, and AI-generated pivot suggestions

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.

Quick Start

bash
# 1. Install
uvx idea-reality-mcp

# 2. Add to your agent
claude mcp add idea-reality -- uvx idea-reality-mcp   # Claude Code

3. Ask 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.

Claude Desktop / Cursor — add to config JSON:

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 · Cursor .cursor/mcp.json

Smithery (remote, no local install):

bash
npx -y @smithery/cli install idea-reality-mcp --client claude

Setup & Configuration

First-time guided setup:

bash
idea-reality setup

This walks you through:

  1. Terms acceptance — data collection policy and disclaimer
  2. Platform detection — auto-detects Claude Desktop, Claude Code, Cursor, Windsurf, Cline
  3. Config generation — prints the exact JSON snippet for your platform
  4. Health check — verifies MCP server, tools, and scoring engine

Platform Configs

bash
idea-reality config              # interactive menu
idea-reality config claude_code  # auto-installs via CLI
idea-reality config cursor       # prints Cursor config
idea-reality config raw_json     # generic MCP JSON

Supported: Claude Desktop · Claude Code · Cursor · Windsurf · Cline · Smithery · Docker

Health Check

bash
idea-reality doctor        # core checks (~2s)
idea-reality doctor --full # + GitHub API, all 6 sources, Anthropic API

Usage

MCP tool call (any MCP-compatible agent):

json
{
  "tool": "idea_check",
  "arguments": {
    "idea_text": "a CLI tool that converts Figma designs to React components",
    "depth": "deep"
  }
}

REST API (no MCP required):

bash
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"}'

Python:

python
import httpx

resp = httpx.post("https://idea-reality-mcp.onrender.com/api/check", json={
    "idea_text": "AI code review tool",
    "depth": "deep"
})
print(resp.json()["reality_signal"])  # 0-100

Free. No API key required.

Why not just Google it?

Your AI agent never Googles anything before it starts building. idea_check runs inside your agent — it triggers automatically whether you remember or not.

GoogleChatGPTidea-reality-mcp
Who runs itYou, manuallyYou, manuallyYour agent, automatically
Output10 blue links"Sounds promising!"Score 0-100 + evidence
SourcesWeb pagesNone (LLM)GitHub + HN + npm + PyPI + PH + SO
PriceFreePaywallFree & open-source (MIT)

Modes

ModeSourcesUse case
quick (default)GitHub + HNFast sanity check, < 3 seconds
deepGitHub + HN + npm + PyPI + Stack OverflowFull competitive scan
SourceQuickDeep
GitHub repos60%22%
GitHub stars20%9%
Hacker News20%14%
npm—18%
PyPI—13%
Stack Overflow—10%

If a source is unavailable, its weight is redistributed automatically — so the deep-mode weights above are renormalised over the sources that actually answered.

Product Hunt was removed on 2026-07-17. It had carried 14% of the deep-mode weight since launch and had never returned a single result: the adapter asked for posts(search: $query), and Product Hunt's API has no text search on posts at all (Field 'posts' doesn't accept argument 'search'). Its weight is now redistributed to sources that answer. If you need it back, it needs a real search surface — not a token.

Tool schema

idea_check

ParameterTypeRequiredDescription
idea_textstringyesNatural-language description of idea
depth"quick" | "deep"no"quick" = GitHub + HN (default). "deep" = all 6 sources
json
{
  "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": "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..."
  ]
}

CI: Auto-check on Pull Requests

Use idea-check-action to validate feature proposals:

yaml
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

bash
export GITHUB_TOKEN=ghp_...        # Higher GitHub API rate limits

PRODUCTHUNT_TOKEN no longer does anything — the source is disabled and ignores it. Setting it used to be worse than useless: it un-skipped a source whose query the API rejects, so it reported "0 competitors on Product Hunt" into 14% of the deep score.

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
  • v0.6 — Onboarding CLI (idea-reality setup, config, doctor)

Star History

Star History Chart

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

Contributing

See CONTRIBUTING.md (繁體中文).

License

MIT — see LICENSE

Built by Mnemox AI · dev@mnemox.ai

Use idea-reality-mcp MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once idea-reality-mcp is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add idea-reality-mcp as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the idea-reality-mcp MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "idea-reality-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the idea-reality-mcp MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the idea-reality-mcp MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use idea-reality-mcp to help me with this task?
idea-reality-mcp
Sure. I read it.
Here is what I found using idea-reality-mcp.

Frequently asked questions

What is the idea-reality-mcp MCP server used for?

idea-reality-mcp is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use idea-reality-mcp MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use idea-reality-mcp with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use idea-reality-mcp MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With idea-reality-mcp connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect idea-reality-mcp MCP to TypingMind?

idea-reality-mcp runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does idea-reality-mcp MCP provide in TypingMind?

idea-reality-mcp exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use idea-reality-mcp MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If idea-reality-mcp requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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