Steam Trends API
Steam concurrent player trends for any game over time. Free key at trendsapi.ai
التثبيت
أضف هذا إلى إعدادات MCP في عميلك (Claude Desktop: claude_desktop_config.json، وCursor: .cursor/mcp.json، ويستخدم VS Code وغيره الصيغة نفسها «mcpServers»).
claude mcp add --transport http steam-trends-api 'https://steam.api.trendsapi.ai/mcp' --header 'Authorization: <Bearer token. Get your free API key at https://trendsapi.ai>'
{
"mcpServers": {
"steam-trends-api": {
"type": "http",
"url": "https://steam.api.trendsapi.ai/mcp",
"headers": {
"Authorization": "<Bearer token. Get your free API key at https://trendsapi.ai>"
}
}
}
}
التوثيق
مأخوذ من ملف README للمشروع على GitHub ويُحدَّث أسبوعيًا. تفتح الروابط على GitHub.
المحتويات
Steam concurrent-player API
Steam player-interest trends via the Trends API. Monthly CCU history, growth, and live most-played. No Steam Web API key.
Key: trendsapi.ai/#get-key. HTTP contract and every source: trendsapi-ai/trendsapi.
Authentication
pip install trendsapi-steam
export TRENDSAPI_KEY=your_key
Python 3.9+. Same key as the HTTP API.
from trendsapi_steam import TrendsAPI
client = TrendsAPI() # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")
Keyword helpers default to source: "steam". 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 (steam). type is exact (Steam Most Played). Mixing them is a 400.
from trendsapi_steam import TrendsAPI
client = TrendsAPI() # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")
series = client.get_time_series("counter-strike 2")
print(series[-1].date, series[-1].value)
growth = client.get_growth("counter-strike 2", 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("counter-strike 2")
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("counter-strike 2", 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_steam import AsyncTrendsAPI
async def main():
c = AsyncTrendsAPI()
return await asyncio.gather(
c.get_time_series("counter-strike 2"),
c.get_time_series("counter-strike 2", source="google search"),
)
asyncio.run(main())
Each 200 is one billed request.
Pandas
from dataclasses import asdict
import pandas as pd
from trendsapi_steam import TrendsAPI
df = pd.DataFrame(asdict(p) for p in TrendsAPI().get_time_series("counter-strike 2"))
df["date"] = pd.to_datetime(df["date"])
print(df.set_index("date")["value"].resample("ME").mean().tail())
Call (curl)
| Field | Value |
|---|---|
| Endpoint | POST https://api.trendsapi.ai/api |
| Auth | Authorization: Bearer $TRENDSAPI_KEY |
| History | source: steam with get_time_series or get_growth |
| Keyword | Game display name, e.g. counter-strike 2 |
Live type | Steam Most Played |
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":"steam","keyword":"counter-strike 2"}'
Source notes
- The backend resolves the name via Steam store search. AppIDs are not a request field.
- Series is monthly.
valueis 0-100 vs that title, not raw CCU. type: steamis 400.
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/steam-trends.
License
MIT. See LICENSE.
الأسئلة الشائعة
ما هو Steam Trends API؟
Steam concurrent player trends for any game over time. Free key at trendsapi.ai
كيف أثبّت Steam Trends API؟
يعمل كخادم بعيد. في Claude Code: claude mcp add --transport http steam-trends-api 'https://steam.api.trendsapi.ai/mcp' --header 'Authorization: <Bearer token. Get your free API key at https://trendsapi.ai>'. وفي العملاء الآخرين، الصق إعداد JSON من هذه الصفحة في إعدادات MCP الخاصة بهم.
هل يحتاج Steam Trends API إلى مفتاح API؟
نعم. يتطلب Authorization، وتضبطها في إعداداته.
هل Steam Trends API مفتوح المصدر؟
نعم. شيفرته متاحة على GitHub بترخيص MIT.
من يصون Steam Trends API؟
ينشره trendsapi-ai. يدرجه AI.tn لكنه لا يصونه ولا يوصي به.
من سجل MCP الرسمي. الإدراج ليس توصية: راجع شيفرة الخادم وصلاحياته قبل منحه الوصول إلى بياناتك.