Server data from the Official MCP Registry
Amazon product search volume and best-seller trends. Free key at trendsapi.ai
About
Amazon product search volume and best-seller trends. Free key at trendsapi.ai
Remote endpoints: streamable-http: https://amazon.api.trendsapi.ai/mcp
Security Report
Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
Endpoint verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"ai-trendsapi-amazon": {
"url": "https://amazon.api.trendsapi.ai/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Amazon product-search demand API
Amazon search interest and bestseller feeds via the Trends API. Ecommerce research without scrapers.
Key: trendsapi.ai/#get-key. HTTP contract and every source: trendsapi-ai/trendsapi.
Authentication
pip install trendsapi-amazon
export TRENDSAPI_KEY=your_key
Python 3.9+. Same key as the HTTP API.
from trendsapi_amazon import TrendsAPI
client = TrendsAPI() # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")
Keyword helpers default to source: "amazon". Pass source= to hit any other platform with the same client. Official full client (every source, no preset): trendsapi.
Methods
| Method | REST mode | Returns |
|---|---|---|
get_time_series(keyword, source=, data_mode=) | get_time_series | list[TrendsDataPoint] |
get_growth(keyword, percent_growth=, source=, data_mode=) | get_growth | GetGrowthResponse |
get_live(limit=, offset=, category=) | get_top_trends | GetTopTrendsResponse |
get_top_trends(type=, ...) | get_top_trends | GetTopTrendsResponse |
source is lowercase (amazon). type is exact (Amazon Best Sellers Top Rated). Mixing them is a 400.
from trendsapi_amazon import TrendsAPI
client = TrendsAPI() # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")
series = client.get_time_series("standing desk")
print(series[-1].date, series[-1].value)
growth = client.get_growth("standing desk", percent_growth=["3M", "12M"])
print(growth.results[0].growth, growth.results[0].direction)
hot = client.get_live(limit=10)
print(hot.data) # [[1, "..."], ...]
get_time_series
points = client.get_time_series("standing desk")
Each point:
| Field | Always | Meaning |
|---|---|---|
date | yes | YYYY-MM-DD |
value | yes | 0-100 index for this series |
keyword | yes | Echo |
volume | no | Absolute volume when available |
source or datatype | no | Pipeline label |
Python returns list[TrendsDataPoint]. Use .date and .value, not ["date"].
JS returns the same fields as object properties.
get_growth
g = client.get_growth("standing desk", percent_growth=["12M", "3M", "YTD"])
print(g.results[0].growth, g.results[0].direction)
percent_growth default: ["12M"]. Presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M/1Y 18M 24M/2Y 36M/3Y 48M 60M/5Y MTD QTD YTD. Custom: {"name": "Launch", "recent": "2024-06-01", "baseline": "2024-01-01"}.
| Field | Meaning |
|---|---|
search_term | Keyword |
data_source | Source |
results | One object per window (period, growth, direction, dates, values) |
metadata | Counts / success flag |
Several windows still count as one request. Python: growth.results[0].growth. JS: growth.results[0].growth.
get_live
hot = client.get_live(limit=10)
| Field | Meaning |
|---|---|
as_of_ts | Snapshot time |
type | Feed name |
limit, offset, count | Pagination |
data | [rank, label] rows |
Python: hot.data. JS: hot.data. Optional offset= and category= (Amazon Best Sellers by Category, Top Websites only).
Async
import asyncio
from trendsapi_amazon import AsyncTrendsAPI
async def main():
c = AsyncTrendsAPI()
return await asyncio.gather(
c.get_time_series("standing desk"),
c.get_time_series("standing desk", source="google search"),
)
asyncio.run(main())
Each 200 is one billed request.
Pandas
from dataclasses import asdict
import pandas as pd
from trendsapi_amazon import TrendsAPI
df = pd.DataFrame(asdict(p) for p in TrendsAPI().get_time_series("standing desk"))
df["date"] = pd.to_datetime(df["date"])
print(df.set_index("date")["value"].resample("ME").mean().tail())
JavaScript / TypeScript
npm install trendsapi-amazon
Node 18+, Deno, Bun, Workers. Same API key. Field tables above apply.
Methods
| Method | REST mode | Returns |
|---|---|---|
getTimeSeries(keyword, { source, data_mode }) | get_time_series | weekly points |
getGrowth(keyword, { percent_growth, source, data_mode }) | get_growth | growth object |
getLive({ limit, offset, category }) | get_top_trends | live feed |
getTopTrends({ type, ... }) | get_top_trends | live feed |
import { TrendsAPI } from "trendsapi-amazon";
const client = new TrendsAPI({ apiKey: process.env.TRENDSAPI_KEY! });
const series = await client.getTimeSeries("standing desk");
console.log(series.at(-1)?.date, series.at(-1)?.value);
const growth = await client.getGrowth("standing desk", {
percent_growth: ["3M", "12M"],
});
console.log(growth.results[0].growth, growth.results[0].direction);
const live = await client.getLive({ limit: 10 });
console.log(live.data); // [[1, "..."], ...]
Call (curl)
| Field | Value |
|---|---|
| Endpoint | POST https://api.trendsapi.ai/api |
| Auth | Authorization: Bearer $TRENDSAPI_KEY |
| History | source: amazon with get_time_series or get_growth |
| Keyword | Product phrase, e.g. standing desk |
Live type | Amazon Best Sellers Top Rated, Amazon Best Sellers by Category |
curl -sS -X POST https://api.trendsapi.ai/api \
-H "Authorization: Bearer $TRENDSAPI_KEY" \
-H "Content-Type: application/json" \
-d '{"mode":"get_time_series","source":"amazon","keyword":"standing desk"}'
Source notes
valueis a 0-100 search-interest index, not units sold.- Feeds answer what is selling now. Keyword series answer what is searched.
- Google Shopping is a different
source(google shopping).
Errors
| HTTP | Client |
|---|---|
| 200 | Parsed payload. Python dataclasses / JS typed objects |
| 400 | Raises. Fix source or type spelling |
| 401 | Raises. Check TRENDSAPI_KEY |
| 404 | Raises. No series for that keyword. Do not retry |
| 429 | Raises. Quota |
| 5xx | Client retries, then raises |
The HTTP body field is a JSON string. SDKs decode it. Raw curl must parse body a second time.
Site: https://trendsapi.ai/trends/amazon-trends.
License
MIT. See LICENSE.
Reviews
No reviews yet
Be the first to review this server!
More Developer Tools MCP Servers
Fetch
Freeby Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
Git
Freeby Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
Toleno
Freeby Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
mcp-creator-python
Freeby mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.
MCP Marketplace
Freeby mcp-marketplace · Developer Tools
Search and install MCP servers from inside your AI client.
MarkItDown
Freeby Microsoft · Content & Media
Convert files (PDF, Word, Excel, images, audio) to Markdown for LLM consumption
