Provides Amazon search trend data and best seller rankings for keyword demand validation and e-commerce analysis.
Delivers App Store download trends, ranking data, and free/paid app charts for mobile app market analysis.
Provides GitHub trending repositories data for discovering popular open-source projects.
Provides live trend data and search volume indexes from Google Search, including weekly historical data and growth comparisons across multiple timeframes.
Offers Google News trend data and news volume analysis for tracking media coverage.
Provides Google Play app ranking and download trend data.
Delivers IMDb trending content data for film and television popularity analysis.
Provides npm package download trend data for analyzing growth and popularity of JavaScript packages.
Offers Reddit trending topics and keyword search data, including hot posts and world news feeds.
Provides Spotify podcast trend data and popularity metrics.
Offers Steam most-played games data and gaming trend information.
Provides TikTok trending hashtags and search trend data, including growth metrics for keywords across the platform.
Delivers Wikipedia page view trends and search volume data for tracking public interest in topics.
Delivers trending video data and keyword search volume from YouTube, enabling analysis of content momentum and popularity.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Trends MCP What's trending on YouTube right now?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Live trend data for AI agents. Google, TikTok, YouTube, Amazon, Reddit, and 30+ other sources. One MCP connection, one API key.
Get a free API key · Docs · Pricing · Data sources · PyPI · Glama
You: Using TrendsMCP, compare 6-month growth for GLP-1 on Google, TikTok, and Amazon.
Agent: Google Search +84%
TikTok +212%
Amazon +61%Three tools. Normalized 0–100 where the pipeline supports it. No per-platform keys. No scraping on your side.
Same four clients as the site hero. Get a free key first (100 req/mo). Claude and ChatGPT sign you in with OAuth. Cursor and VS Code: click, then put your key from /account if the deeplink used a placeholder.
Client | After you click |
Claude | Connector name and URL are prefilled ( |
Cursor | Approve the MCP install. Replace |
ChatGPT | Enable Developer mode (Profile → Settings → Security). Name |
VS Code | Sign in on the account page and use the VS Code button so the key is included. |
Then ask: Using TrendsMCP, what's trending on Google right now?
Tools · Sources · Feeds · REST · Install in other clients
Related MCP server: Socialcrawl
Hosted MCP at https://api.trendsmcp.ai/mcp. Same Bearer key for POST https://api.trendsmcp.ai/api. This repo also has a stdio adapter for Glama and local hosts.
Tool | Use when | Needs a keyword? |
| History for one keyword on one source | Yes |
| Percent change over 7D–5Y (several windows in one call) | Yes |
| What is ranking on a platform right now | No |
Replace YOUR_API_KEY with the key from your account.
claude mcp add --scope user --transport http trends-mcp https://api.trendsmcp.ai/mcp \
--header "Authorization: Bearer YOUR_API_KEY"~/.cursor/mcp.json (Windows: %USERPROFILE%\.cursor\mcp.json)
{
"mcpServers": {
"trends-mcp": {
"url": "https://api.trendsmcp.ai/mcp",
"transport": "http",
"headers": { "Authorization": "Bearer YOUR_API_KEY" }
}
}
}.vscode/mcp.json or Command Palette → MCP: Add Server. Prefer the account-page VS Code button so the key is wired for you.
{
"servers": {
"trends-mcp": {
"type": "http",
"url": "https://api.trendsmcp.ai/mcp",
"headers": { "Authorization": "Bearer YOUR_API_KEY" }
}
}
}Uses serverUrl, not Cursor’s url + transport. File: ~/.codeium/windsurf/mcp_config.json.
{
"mcpServers": {
"trends-mcp": {
"serverUrl": "https://api.trendsmcp.ai/mcp",
"headers": { "Authorization": "Bearer YOUR_API_KEY" }
}
}
}Remote server, type exactly streamableHttp. See llms-install.md.
{
"mcpServers": {
"trends-mcp": {
"type": "streamableHttp",
"url": "https://api.trendsmcp.ai/mcp",
"headers": { "Authorization": "Bearer YOUR_API_KEY" },
"disabled": false
}
}
}{
"mcpServers": {
"trends-mcp": {
"command": "npx",
"args": [
"-y", "mcp-remote",
"https://api.trendsmcp.ai/mcp",
"--header", "Authorization:${AUTH_HEADER}"
],
"env": { "AUTH_HEADER": "Bearer YOUR_API_KEY" }
}
}
}Settings → Connectors → add https://www.trendsmcp.ai/mcp. This path uses OAuth on www.trendsmcp.ai. Do not put a Bearer key in that connector config.
Hosted HTTP is still the product default. This process lists tools with no key; paid calls need TRENDSMCP_API_KEY and bill the same quota.
pip install -e .
python -m trends_mcp_server{
"mcpServers": {
"trends-mcp": {
"command": "python",
"args": ["-m", "trends_mcp_server"],
"env": { "TRENDSMCP_API_KEY": "YOUR_API_KEY" }
}
}
}Say “using TrendsMCP” so the model picks these tools instead of web search. More clients: docs.
Always-current parameter lists: docs.
get_time_seriesWeekly (or daily) history for one source + keyword. Same name on MCP and REST (mode: "get_time_series"). REST also accepts get_trends as an alias.
Argument | Required | Notes |
| yes | Format depends on source (table below) |
| yes | One source per call. Lowercase catalog names |
| no | REST only. |
Index is 0–100 where the pipeline supports it (100 = peak in the returned window). volume is present when that source has an absolute series.
get_growthPoint-to-point percent change. Several windows in one call still count as one request for that source + keyword.
Argument | Required | Notes |
| yes | Same formats as |
| yes | One source, or a comma-separated list ( |
| no | Default |
Presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M 1Y 18M 24M 2Y 36M 3Y 48M 60M 5Y MTD QTD YTD.
get_top_trendsLive ranked list. No keyword. On MCP, type is required and must match the feed name exactly (including capitals). On REST, omit type only if you intend to pull every feed (billed per feed).
Argument | Required on MCP | Notes |
| yes | See live feeds |
| no | Default 25, max 200 |
| no | Pagination |
| for some types | Amazon / Google Trends / Top Websites / Substack / TikTok hashtag category boards |
| no |
|
| no | With |
Using TrendsMCP, what's trending on Google right now?
Using TrendsMCP, what are the hottest Reddit posts right now?
Using TrendsMCP, compare 6-month growth for creatine gummies on Google, TikTok, and Amazon.
Using TrendsMCP, show Google Search history for protein soda.
Via TrendsMCP, pull npm download history for langchain.
Using TrendsMCP, show Steam concurrent players for Elden Ring.
Via TrendsMCP, Android downloads for com.openai.chatgpt.
Using TrendsMCP, fastest-climbing Amazon best sellers in Toys Games this week.source on get_time_series / get_growth. Not the same strings as type on live feeds.
| Signal |
|
| Search volume | Any phrase |
| Image search volume | Any phrase |
| News-tab volume | Any phrase |
| Shopping-tab volume | Any phrase |
| YouTube search volume | Any phrase |
| Hashtag volume | Hashtag or topic ( |
| Subreddit attention | Name only, no |
| Product search volume | Product or category |
| Page views | Article title or topic |
| Mention volume | Any phrase |
| News tone | Any phrase |
| Android downloads | Play bundle id, e.g. |
| Android chart position | Bundle id |
| Weekly downloads | Exact package name ( |
| Monthly concurrent players | Game display name ( |
source: "Google Trends" is invalid. Use google search for history and type: "Google Trends" for the live board.
type on get_top_trends. Copy the name exactly.
| Board |
| Google searches now |
| Needs |
| Google News stories |
| Hashtags |
| Needs |
| In-app searches |
| Videos |
| Topics on X |
| Front page |
| r/worldnews |
| Most-viewed articles |
| Top-rated sellers |
| Needs |
| iOS charts |
| Play chart |
| Global traffic rank; optional |
| Podcasts |
| Live players |
| Newsletters |
| Daily trending repos |
| Movie activity |
| Books |
Category name lists: docs.
iOS charts, GitHub repos, Spotify, IMDb, Open Library, Substack, and Top Websites are feeds, not source values. There is no source: "web traffic".
curl -sS -X POST https://api.trendsmcp.ai/api \
-H "Authorization: Bearer $TRENDSMCP_API_KEY" \
-H "Content-Type: application/json" \
-d '{"mode":"get_top_trends","type":"Google Trends","limit":5}'import os, requests
r = requests.post(
"https://api.trendsmcp.ai/api",
headers={"Authorization": f"Bearer {os.environ['TRENDSMCP_API_KEY']}"},
json={"mode": "get_growth", "source": "google search", "keyword": "bitcoin", "percent_growth": ["3M", "12M"]},
)
print(r.json())Python client: pip install trendsmcp.
Plan | Requests / month | Price |
Free | 100 | $0 |
Starter | 1,000 | $19 |
Pro | 5,000 | $49 |
Business | 25,000 | $199 |
Annual billing is 20% less. Same source catalog on every plan. Free history and “top N” caps are on pricing. Failed calls are not billed. Over quota returns 429 / rate_limited (no surprise overages).
One billed request:
get_time_series: one source + keyword
get_growth: one source + keyword (all windows in that call included)
get_top_trends: per type (and pagination as documented)
Status | Meaning |
400 | Bad or missing |
401 | Missing or invalid key |
404 | No series for that keyword + source |
429 | Monthly cap |
500 | Upstream or internal error |
Do not commit keys. Claude.ai connectors use OAuth; other clients use Authorization: Bearer ….
Region / geo breakdown, related queries, or related topics
Hourly series
get_time_series across several sources in one call (use get_growth with a comma-separated source list, or several get_time_series calls)
Inventing feed names: MCP type must match the table
pip install -e .
python -m trends_mcp_serverCI: .github/workflows/ci.yml. Security: SECURITY.md. Issues: github.com/trendsmcp-ai/Trends-MCP/issues.
TrendWatch (alerts in your own GitHub repo)
MIT © Trends MCP
Point-to-point growth for a keyword on one or more sources. Each window is a preset string (12M, 3M, YTD, and the other listed periods). Values are on a 0-100 scale, plus absolute volume when available. Prefer this over get_time_series for growth questions. app downloads and app rankings are keyword sources (Android bundle ID). They are not the App Store / Google Play live boards on get_top_trends. If the request is rate limited or the monthly quota is used up, tell the user their plan limit is reached.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | One source, or comma-separated sources (e.g. 'amazon, tiktok, youtube'). Valid: 'google search', 'google images', 'google news', 'google shopping', 'youtube', 'wikipedia', 'tiktok', 'reddit', 'amazon', 'news sentiment', 'news volume', 'npm', 'python', 'steam', 'app downloads', 'app rankings'. | |
| keyword | Yes | What to look up. The string format is required by source. Standard sources (google search, google images, google news, google shopping, youtube, wikipedia, tiktok, reddit, amazon, news sentiment, news volume): any name or phrase, e.g. 'nike'. npm: exact npmjs.com package name, case-sensitive. Right: 'react', '@babel/core'. Wrong: 'React', 'React.js'. python: exact PyPI project name. Right: 'pandas', 'requests'. Wrong: 'Pandas'. steam: game display name in plain English, not a Steam App ID. Right: 'Elden Ring', 'CS2'. First Steam store search result wins, so use an unambiguous name. app downloads and app rankings: Android bundle ID only (the id= value on Google Play). Right: 'com.openai.chatgpt', 'com.whatsapp'. Wrong: 'ChatGPT', 'WhatsApp', an iOS App Store ID, or a bundle ID that is not Android. Find it at play.google.com/store/apps/details?id=THIS_PART. If the request includes app downloads or app rankings with other sources, keyword must still be the Android bundle ID. | |
| percent_growth | No | Growth windows. Default if omitted: ['12M']. Each item must be a preset string: '7D', '1W', '14D', '2W', '30D', '1M', '2M', '3M', '6M', '9M', '12M', '1Y', '18M', '24M', '2Y', '36M', '3Y', '48M', '4Y', '60M', '5Y', 'MTD', 'QTD', 'YTD'. Every preset is a two-date comparison. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds value by disclosing the 0-100 value scale, absolute volume 'when available,' preset growth windows, and the correct user-facing action when rate limits or quotas are hit — none of which are in the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action and then adds windows, output scale, sibling disambiguation, and error handling in logical order. Every sentence earns its place; there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the rich input schema, output schema, and safety annotations, the description is complete. It covers selection criteria, source caveats, value semantics, and quota/rate-limit behavior, leaving no critical gap for an agent deciding whether and how to call the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description's remarks about preset windows and Android bundle IDs largely restate schema content rather than adding new parameter-level semantics, so it does not exceed the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Point-to-point growth for a keyword on one or more sources.' It also explicitly distinguishes itself from both siblings by recommending it over get_time_series for growth questions and clarifying that app downloads/rankings are not the live boards on get_top_trends.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives direct selection guidance: 'Prefer this over get_time_series for growth questions.' It also clarifies a not-this case by stating app downloads/rankings are keyword sources, not get_top_trends live boards, and provides explicit handling for rate limits or quota exhaustion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Full historical series for one keyword and one source (0-100 values, plus volume when available). Use for charting or custom math. Not for live 'what's trending now' boards (use get_top_trends). For most growth questions, use get_growth. If the request is rate limited or the monthly quota is used up, tell the user their plan limit is reached.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | Exactly one source per request. Valid: 'google search', 'google images', 'google news', 'google shopping', 'youtube', 'wikipedia', 'tiktok', 'reddit', 'amazon', 'news sentiment', 'news volume', 'npm', 'python', 'steam', 'app downloads', 'app rankings'. | |
| keyword | Yes | What to look up. The string format is required by source. Standard sources (google search, google images, google news, google shopping, youtube, wikipedia, tiktok, reddit, amazon, news sentiment, news volume): any name or phrase, e.g. 'tesla'. npm: exact npmjs.com package name, case-sensitive. Right: 'react', '@babel/core'. Wrong: 'React', 'React.js'. python: exact PyPI project name. Right: 'pandas', 'requests'. Wrong: 'Pandas'. steam: game display name in plain English, not a Steam App ID. Right: 'Elden Ring', 'CS2'. First Steam store search result wins, so use an unambiguous name. app downloads and app rankings: Android bundle ID only (the id= value on Google Play). Right: 'com.openai.chatgpt', 'com.whatsapp'. Wrong: 'ChatGPT', 'WhatsApp', an iOS App Store ID, or a bundle ID that is not Android. Find it at play.google.com/store/apps/details?id=THIS_PART. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint; the description adds value beyond them by disclosing the 0-100 value range, optional volume inclusion, and rate-limit/quota behavior with a concrete user-facing instruction. Nothing contradicts the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded with the core behavior, then gives usage context, sibling routing, and rate-limit handling. Every sentence earns its place and there is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The combination of description, annotations, rich schema, and output schema fully equips an agent to select, invoke, and handle results. It covers scope, alternatives, result shape, and quota behavior with no meaningful gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the schema itself thoroughly documents both parameters, including valid sources and per-source keyword formats. The description only reinforces 'one keyword and one source' without adding new parameter-level meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Full historical series for one keyword and one source', which names a specific resource and scope. It also actively distinguishes itself from siblings by saying 'Not for live...' and 'use get_growth', so an agent can tell it apart immediately.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when this tool is appropriate ('Use for charting or custom math') and when it is not, naming the alternatives get_top_trends and get_growth. This is direct, unambiguous routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Live top-trending board for exactly one feed type. No keyword. For 'Amazon Best Sellers by Category', 'Google Trends by Category', 'Top Websites', and 'Substack by Category', always pass category. Default sort is current rank. Use sort='rank_change' for climbers vs a prior snapshot (window 1d, 3d, 7d, 14d, or 30d). App Store Top Free, App Store Top Paid, and Google Play are live store boards, not keyword lookups. For an app's history use get_growth or get_time_series with source app downloads or app rankings and an Android bundle ID. Do not use get_time_series for live boards. If the request is rate limited or the monthly quota is used up, tell the user their plan limit is reached.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | How to rank the board. 'rank' (default): current leaders. 'rank_change': biggest climbers vs a prior snapshot. Mover rows include rank, keyword, prev_rank, and rank_change. | rank |
| type | Yes | Exactly one live feed. Valid: 'Amazon Best Sellers Top Rated', 'Amazon Best Sellers by Category', 'App Store Top Free', 'App Store Top Paid', 'GitHub', 'Google News Top News', 'Google Play', 'Google Trends', 'Google Trends by Category', 'IMDb MOVIEmeter', 'Open Library Trending Books', 'Reddit Hot Posts', 'Reddit World News', 'Top Websites', 'Spotify Top Podcasts', 'Steam Most Played', 'Substack', 'Substack by Category', 'TikTok Trending Hashtags', 'TikTok Trending Searches', 'Wikipedia Trending', 'X (Twitter) Trending', 'YouTube Trending'. | |
| limit | No | Max rows to return. Default 25, min 1, max 200. | |
| offset | No | Rows to skip for pagination. Default 0. | |
| window | No | Lookback used only when sort is 'rank_change'. One of '1d', '3d', '7d', '14d', '30d'. Default '30d'. Short windows only work on daily feeds; weekly and monthly feeds return a note pointing to a longer window. | 30d |
| category | No | Pass this whenever type is 'Amazon Best Sellers by Category', 'Google Trends by Category', 'Top Websites', or 'Substack by Category'. Use the official name. Without it those feeds mix every board. Only omit on a first pull to learn the official names. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool safe/read-only, and the description adds substantial behavioral context: default sort behavior, rank_change window semantics, live-board vs keyword behavior, and quota/rate-limit error handling. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense but every sentence carries decision-relevant information, with the core purpose front-loaded. It avoids filler while covering routing, parameter relationships, and error behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex multi-feed tool with six parameters and an output schema, the description covers the essential selection rules, category requirement, sort/window semantics, sibling routing, and quota handling. Nothing critical is missing for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaningful cross-parameter guidance: when category is mandatory, which sort/window combination is valid, and how the live-board types differ from keyword lookups. This goes beyond the schema's individual field descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a live top-trending board for exactly one feed type and explicitly distinguishes it from keyword lookups. It also differentiates from sibling tools by framing the tool as current/live rather than historical.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use guidance (live boards), when-not-to-use guidance (app history), and names the alternatives (get_growth, get_time_series). It also specifies mandatory category passing for certain feed types and warns against using get_time_series for live boards, leaving no ambiguity about routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.1get_growthget_time_seriesget_top_trendsEach tool has a clearly distinct purpose: get_growth measures point-to-point keyword growth, get_time_series returns full historical series, and get_top_trends handles live top-trending boards without a keyword. Cross-references like 'prefer this over get_time_series' further reduce ambiguity.
All tool names follow a consistent get_<objet> pattern with clear, descriptive nouns: get_growth, get_time_series, get_top_trends. There are no mixed conventions or vague verbs.
Three tools is a tight, well-scoped set for trends data: historical series, growth calculations, and live rankings. Each tool earns its place with no redundant or filler endpoints.
The set covers the core domains of trend analysis well: growth, time series, and live boards. A minor gap is that there is no explicit tool for enumerating supported sources, periods, or categories, though the descriptions largely compensate.
Twitter/X, Instagram, Reddit & TikTok data for AI agents. Billions of posts. No API keys.
Cross-platform social trend signals from TikTok, YouTube, Reddit and X. Free key at trendsapi.ai
Connect your AI to all your data - 200+ sources, intelligently filtered, compliance-ready.
Social listening for AI: query brand mentions across 15+ platforms, run analytics, manage keywords.
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