mcpField
S
Steam Trends API

Steam Trends API

Remote
trendsapi.aiGames & Entertainment0Updated 10w ago

About Steam Trends API

Steam Trends API is an API and Python SDK for developers analyzing interest in Steam games. It provides monthly history, growth metrics, and live rankings without requiring a Steam Web API key.

Key features

  1. 01Retrieve monthly trend series
  2. 02Calculate growth across time windows
  3. 03Fetch live popular-game rankings
  4. 04Use synchronous or asynchronous Python clients

Use cases

  1. 01Compare game interest across periods
  2. 02Check currently popular Steam games
  3. 03Prepare trend data in Pandas

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://steam.api.trendsapi.ai/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://steam.api.trendsapi.ai/mcpAuth required

Tools

Details

From the project README

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.

License: MIT PyPI Python

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

MethodREST modeReturns
get_time_series(keyword, source=, data_mode=)get_time_serieslist[TrendsDataPoint]
get_growth(keyword, percent_growth=, source=, data_mode=)get_growthGetGrowthResponse
get_live(limit=, offset=, category=)get_top_trendsGetTopTrendsResponse
get_top_trends(type=, ...)get_top_trendsGetTopTrendsResponse

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:

FieldAlwaysMeaning
dateyesYYYY-MM-DD
valueyes0-100 index for this series
keywordyesEcho
volumenoAbsolute volume when available
source or datatypenoPipeline 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"}.

FieldMeaning
search_termKeyword
data_sourceSource
resultsOne object per window (period, growth, direction, dates, values)
metadataCounts / 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)
FieldMeaning
as_of_tsSnapshot time
typeFeed name
limit, offset, countPagination
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)

FieldValue
EndpointPOST https://api.trendsapi.ai/api
AuthAuthorization: Bearer $TRENDSAPI_KEY
Historysource: steam with get_time_series or get_growth
KeywordGame display name, e.g. counter-strike 2
Live typeSteam 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. value is 0-100 vs that title, not raw CCU.
  • type: steam is 400.

Errors

HTTPClient
200Parsed payload. Python dataclasses / JS typed objects
400Raises. Fix source or type spelling
401Raises. Check TRENDSAPI_KEY
404Raises. No series for that keyword. Do not retry
429Raises. Quota
5xxClient 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.

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