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app-store-trends-mcp

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App Store trends as an MCP tool for Claude, Cursor, VS Code and more. Weekly series, growth percentages, and live App Store top charts. Powered by trendsmcp.ai

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Last scanned: 8/19/2026
Install in Claude Code / Claude Desktop
Method: pip / Python · app-store-trends-mcp
Claude Code CLI
claude mcp add app-store-trends-mcp -- python -m app-store-trends-mcp
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "app-store-trends-mcp": {
      "command": "python",
      "args": ["-m", "app-store-trends-mcp"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Install first: pip install app-store-trends-mcp
Casos de uso

Resumen de MCP Servers

# app-store-trends-mcp

App download trends as an MCP tool. Plug into Claude, Cursor, or any MCP-compatible AI host. Weekly series, growth percentages, and live top charts.

Powered by **[trendsmcp.ai](https://trendsmcp.ai)** — one API key, one client, **30+ data sources**: Google Search, YouTube, TikTok, Reddit, Amazon, Wikipedia, App Store, Steam, npm, news volume, news sentiment, live trending feeds, and more. No separate credentials per platform.

**[Get your free API key → trendsmcp.ai](https://trendsmcp.ai)** — 100 free requests/month, no credit card.

📖 **[Full API docs → trendsmcp.ai/docs](https://trendsmcp.ai/docs)**

Updated for 2026. Works with Python 3.8 through 3.13.

## Use as an MCP tool

Add to your `mcp.json` (Claude Desktop, Cursor, Windsurf, VS Code, or any MCP host):

```json
{
  "mcpServers": {
    "trends-mcp": {
      "url": "https://api.trendsmcp.ai/mcp",
      "transport": "http",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}
```

Get your free key at **[trendsmcp.ai](https://trendsmcp.ai)**. Full setup instructions for Claude, Cursor, Windsurf, and VS Code at **[trendsmcp.ai/docs](https://trendsmcp.ai/docs)**.

---

## No scraping. No 429 errors. No proxies.

If you have used pytrends or similar scrapers before, you know the problems: random `429 Too Many Requests` blocks, broken pipelines at 2am, time.sleep() hacks, proxy rotation costs, and a library that is now **archived** because Google explicitly flags scrapers at the protocol level.

trendsmcp is the managed alternative. We run the data infrastructure. You call a REST endpoint.

### pytrends alternative for App Store data

| | Scrapers / pytrends | trendsmcp |
|---|---|---|
| 429 rate limit errors | constant | never |
| Proxy required | often | never |
| Breaks on platform changes | yes, regularly | no |
| Data sources covered | 1 (Google only) | 30+ |
| Absolute volume estimates | no | yes |
| Cross-platform growth | no | yes |
| Async support | no | yes |
| Actively maintained | no (archived) | yes |
| Free tier | no | yes, 100 req/month |

---

## Install

```bash
pip install app-store-trends-mcp
```

Zero system dependencies. Python 3.8 or later. Uses `httpx` under the hood.

---

## Quick start

```python
from app_store_trends_mcp import TrendsMcpClient, SOURCE

client = TrendsMcpClient(api_key="YOUR_API_KEY")

# 5-year weekly time series — no sleep(), no proxies, no 429s
series = client.get_trends(source=SOURCE, keyword="com.openai.chatgpt")
print(series[0])
# TrendsDataPoint(date='2026-03-28', value=72, keyword='com.openai.chatgpt', source='app downloads')

# Period-over-period growth
growth = client.get_growth(
    source=SOURCE,
    keyword="com.openai.chatgpt",
    percent_growth=["3M", "1Y"],
)
print(growth.results[0])
# GrowthResult(period='3M', growth=14.5, direction='increase', ...)

# What's trending right now (across all live platforms)
trending = client.get_top_trends(limit=10)
print(trending.data)
# [[1, 'topic one'], [2, 'topic two'], ...]
```

---

## Async support

```python
import asyncio
from app_store_trends_mcp import AsyncTrendsMcpClient, SOURCE

async def main():
    client = AsyncTrendsMcpClient(api_key="YOUR_API_KEY")
    series = await client.get_trends(source=SOURCE, keyword="com.openai.chatgpt")
    print(series[0])

asyncio.run(main())
```

Query multiple platforms concurrently with one key:

```python
google, youtube, reddit, amazon, tiktok = await asyncio.gather(
    client.get_trends(source="google search", keyword="com.openai.chatgpt"),
    client.get_trends(source="youtube",       keyword="com.openai.chatgpt"),
    client.get_trends(source="reddit",        keyword="com.openai.chatgpt"),
    client.get_trends(source="amazon",        keyword="com.openai.chatgpt"),
    client.get_trends(source="tiktok",        keyword="com.openai.chatgpt"),
)
```

---

## Use cases

- **SEO research**: track keyword search volume trends across Google Search, Google News, and Google Images before publishing content
- **Market research**: measure consumer demand signals on Amazon and Google Shopping before entering a product category
- **Investment research**: monitor Reddit discussion volume, news sentiment, and Wikipedia page view spikes as leading indicators
- **Content strategy**: find what is growing on YouTube and TikTok before topics peak and competition saturates them
- **Competitor tracking**: compare brand search volume growth across platforms over custom date ranges
- **App analytics**: track App Store interest and app download estimates alongside Reddit and news buzz

---

## Works with

- **Claude** (via MCP — [trendsmcp.ai/docs](https://trendsmcp.ai/docs))
- **Cursor** (via MCP — [trendsmcp.ai/docs](https://trendsmcp.ai/docs))
- **ChatGPT** (via MCP — [trendsmcp.ai/docs](https://trendsmcp.ai/docs))
- **Windsurf** (via MCP — [trendsmcp.ai/docs](https://trendsmcp.ai/docs))
- **VS Code Copilot** (via MCP — [trendsmcp.ai/docs](https://trendsmcp.ai/docs))
- **LangChain**: pass `TrendsMcpClient` output directly as tool results or context
- **CrewAI**: wrap any method as a `Tool` and drop it into your crew
- **AutoGen**: register as a callable tool for any agent
- **LlamaIndex**: use trend series as structured data nodes for retrieval
- **Pandas**: each `get_trends()` response converts to a DataFrame in one line

---

## Methods

### `get_trends(source, keyword, data_mode=None)`

Returns a historical time series for a keyword. Defaults to 5 years of weekly data. Pass `data_mode="daily"` for the last 30 days at daily granularity.

### `get_growth(source, keyword, percent_growth, data_mode=None)`

Calculates percentage growth between two points in time. Pass preset strings or `CustomGrowthPeriod` objects.

**Growth presets:** `7D` `14D` `30D` `1M` `2M` `3M` `6M` `9M` `12M` `1Y` `18M` `24M` `2Y` `36M` `3Y` `48M` `60M` `5Y` `MTD` `QTD` `YTD`

### `get_top_trends(type=None, limit=None)`

Returns today's live trending items. Omit `type` to get all feeds at once.

**Available live feeds:** `Google Trends` `Google News Top News` `YouTube Trending` `TikTok Trending Hashtags` `X (Twitter) Trending` `Reddit Hot Posts` `Reddit World News` `Wikipedia Trending` `Amazon Best Sellers Top Rated` `Amazon Best Sellers by Category` `App Store Top Free` `App Store Top Paid` `Google Play` `Spotify Top Podcasts` `Top Websites`

---

## All 30+ data sources

One API key. One client. Every platform. No separate credentials for each.

| source | What it measures |
|---|---|
| `"google search"` | Google Search volume |
| `"google images"` | Google Images search volume |
| `"google news"` | Google News search volume |
| `"google shopping"` | Google Shopping purchase intent |
| `"youtube"` | YouTube search volume |
| `"tiktok"` | TikTok hashtag volume |
| `"reddit"` | Reddit subreddit subscribers over time |
| `"amazon"` | Amazon product search volume |
| `"wikipedia"` | Wikipedia page views |
| `"news volume"` | News article mention count |
| `"news sentiment"` | News sentiment score (positive/negative) |
| `"app downloads"` | Mobile app download/install estimates (Android) |
| `"npm"` | npm package weekly downloads |
| `"steam"` | Steam concurrent player count |

All values normalized 0–100 so you can compare across platforms directly.

---

## Error handling

```python
from app_store_trends_mcp import TrendsMcpClient, TrendsMcpError, SOURCE

client = TrendsMcpClient(api_key="YOUR_API_KEY")

try:
    series = client.get_trends(source=SOURCE, keyword="com.openai.chatgpt")
except TrendsMcpError as e:
    print(e.status)   # e.g. 429 if you exceed your plan quota
    print(e.code)     # e.g. "rate_limited"
    print(e.message)
```

---

## Frequently asked questions

**Does this scrape App Store?**
No. trendsmcp runs managed data infrastructure. Your Python code makes a single authenticated REST call. No scraping, no Selenium, no cookies, no proxies required.

**Do I need a App Store developer account, OAuth token, or platform API key?**
No. One trendsmcp API key gives you access to all 30+ data sources.

**Will it break when App Store changes its backend?**
No. API stability is our responsibility. If something changes upstream, we update the backend. Your code keeps working.

**Can I query multiple platforms with the same key?**
Yes. One key covers every data source. Switch `source` to any of the 30+ values listed above.

**Is there a free tier?**
Yes, 100 requests per month, no credit card required. [Get your key at trendsmcp.ai](https://trendsmcp.ai).

**Can I use this in production data pipelines?**
Yes. The client is stateless, thread-safe, and supports async for concurrent queries across multiple platforms.

---

## Related packages

- [trendsmcp](https://pypi.org/project/trendsmcp/) — core package, all 30+ data sources
- [youtube-trends-api](https://pypi.org/project/youtube-trends-api/) / [youtube-trends-mcp](https://pypi.org/project/youtube-trends-mcp/) / [youtube-trends-agent](https://pypi.org/project/youtube-trends-agent/)
- [reddit-trends-api](https://pypi.org/project/reddit-trends-api/) / [reddit-trends-mcp](https://pypi.org/project/reddit-trends-mcp/) / [reddit-trends-agent](https://pypi.org/project/reddit-trends-agent/)
- [google-search-trends-api](https://pypi.org/project/google-search-trends-api/) / [google-search-trends-mcp](https://pypi.org/project/google-search-trends-mcp/) / [google-search-trends-agent](https://pypi.org/project/google-search-trends-agent/)
- [amazon-trends-api](https://pypi.org/project/amazon-trends-api/) / [amazon-trends-mcp](https://pypi.org/project/amazon-trends-mcp/) / [amazon-trends-agent](https://pypi.org/project/amazon-trends-agent/)
- [tiktok-trends-api](https://pypi.org/project/tiktok-trends-api/) / [tiktok-trends-mcp](https://pypi.org/project/tiktok-trends-mcp/) / [tiktok-trends-agent](https://pypi.org/project/tiktok-trends-agent/)
- [wikipedia-trends-api](https://pypi.org/project/wikipedia-trends-api/) / [wikipedia-trends-mcp](https://pypi.org/project/wikipedi
ai-toolsanalyticsapiapp-downloadsapp-storeasyncclaudecursoriosllm-toolsmarket-researchmcpmobilemodel-context-protocolno-scrapingpypipythonsearch-volumetrend-datatrendsmcp

Lo que la gente pregunta sobre app-store-trends-mcp

¿Qué es trendsmcp-ai/app-store-trends-mcp?

+

trendsmcp-ai/app-store-trends-mcp es mcp servers para el ecosistema de Claude AI. App Store trends as an MCP tool for Claude, Cursor, VS Code and more. Weekly series, growth percentages, and live App Store top charts. Powered by trendsmcp.ai Tiene 0 estrellas en GitHub y su última actualización registrada es del 2026-08-09.

¿Cómo se instala app-store-trends-mcp?

+

Puedes instalar app-store-trends-mcp clonando el repositorio (https://github.com/trendsmcp-ai/app-store-trends-mcp) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar trendsmcp-ai/app-store-trends-mcp?

+

Nuestro agente de seguridad ha analizado trendsmcp-ai/app-store-trends-mcp y le ha asignado un Trust Score de 95/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene trendsmcp-ai/app-store-trends-mcp?

+

trendsmcp-ai/app-store-trends-mcp es mantenido por trendsmcp-ai. La última actividad registrada en GitHub es del 2026-08-09, con 0 issues abiertos.

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