Trend data API pricing comparison
Trend data API pricing is rarely what it appears. SerpApi charges per request with expiring credits. Meltwater and Brandwatch require enterprise contracts with no public pricing. Exploding Topics locks the API behind higher-tier plans. This page breaks down the true cost of each major trend data option in 2026 - including what you get per dollar, what expires, and what the hidden costs are.
Free API access
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100 free requests per month. No credit card, no setup fee.
Replaced my manual Google Trends scraper in an afternoon. The data is clean and the latency is surprisingly low for a free tier.
We use it for keyword trend reports. The free monthly quota keeps us batching queries for weekly digests. Upgrading is there when we need more headroom.
Hooked it into my MCP server in like 20 minutes. The JSON response is well-structured and the docs are solid. Exactly what I needed.
We pipe weekly series into BigQuery for a few brand cohorts. Compared to maintaining our old Selenium job, this is boring in the best way. Uptime has been solid.
Great for slide-ready trend screenshots when leadership asks why we are prioritizing a feature. I wish the dashboard had saved views, but the API side is great.
Running it from Cursor with the MCP config took one try. I am not a trends person, but my side project now emails me when a niche keyword spikes hard week over week.
Using the growth endpoints to sanity-check retail names before I write up notes. Occasionally the normalization differs from what I see in the raw Google UI, but it is consistent run to run.
Pulling multi-source ranked lists into a notebook is straightforward. Error payloads are actually readable when I fat-finger a parameter, which matters more than people admit.
Does what it says. I knocked a star because onboarding assumed I already knew MCP wiring; a copy-paste block for Claude Desktop would have saved me 15 minutes.
We track TikTok hashtag momentum against paid spend in a Looker sheet. Not glamorous work, but it is the first tool my team did not argue about during rollout.
Retries are predictable and I have not seen weird HTML in responses (looking at you, scrapers). Would pay for a team key rotation flow, but for now we rotate manually.
Quick checks on retail buzz before we dig into filings. Not a silver bullet, but it is faster than opening twelve browser tabs and reconciling by hand.
Helpful for spotting whether a topic is a one-day meme or sticking around. I still cross-check with Search Console, but this gets me 80% of the signal in one call.
I demo this in workshops when people ask how to ground LLM answers in something fresher than training data. The MCP angle lands well with engineers who hate glue code.
Solid for client reporting. Billing is clear enough that finance stopped asking me what line item this is. Minor nit: peak hours can feel a touch slower, still acceptable.
I wired this behind a small CLI for contributors who want trend context in issues. Keeping the surface area tiny matters for OSS, and the schema has not churned on me yet.
Daily pulls for a 30-day window go straight into our internal scoreboard. Stakeholders finally stopped debating whose screenshot of Trends was newer.
We are pre-revenue, so free tier discipline matters. I hit the cap once during a brainstorm where everyone wanted to try random keywords. Learned to batch smarter.
Security review passed without drama: HTTPS, scoped keys, no bizarre third-party redirects in the chain we could find. That is rarer than vendors think.
I do not need this daily, but when App Store rank shifts look weird, having Reddit and news context in one place saves me from context switching across six apps.
I use it to see if a story is genuinely blowing up or just loud on one platform. It is not a replacement for reporting, but it keeps my ledes honest.
We moved off a brittle Playwright script that broke every time Google shuffled markup. Same data shape every week now, which is all I wanted from life.
Seasonal demand spikes line up with what we see in Amazon search interest here. Merch team stopped sending me screenshots from random tools that never matched.
Solid for client decks. I docked one star only because I still export to Sheets manually; a direct connector would be nice someday.
Steam concurrents plus Reddit chatter in one workflow beats our old spreadsheet ritual before milestone reviews.
Quick pulse on whether a feature name is confusing people in search before we ship copy. Cheap sanity check compared to a full survey.
Monitored from Grafana via a thin wrapper. p95 stayed under our SLO budget last month. One noisy day during a holiday but nothing alarming.
Narrative fights in meetings got shorter once we could point at the same trend line everyone agreed on. Sounds silly until you have lived through it.
Using normalized series as a weak prior in a forecasting experiment. Citation-friendly timestamps in the payload made reproducing runs less painful.
Approved for our pilot group after a quick vendor review. Would love SAML, not a blocker for our size.
YouTube search interest plus TikTok hashtags in one place helps me explain why a sponsor should care about a vertical without hand-waving.
Cron job hits the API before standup; Slack gets a compact summary. Took an afternoon to wire, has been stable for two quarters.
Useful for public-interest topics where search interest is a rough proxy for attention. I still triangulate with primary sources; this is one signal among several.
Runs in a VPC egress-only subnet with allowlisted domains. Fewer exceptions to explain to auditors than our last vendor.
Spotting when a topic is about to flood Discord saves my team from reactive moderation fires. Not perfect, but directionally right often enough.
For lean teams the ROI story writes itself. I would not build an in-house scraper for this anymore unless compliance forced it.
Examples in the docs match what the MCP actually returns. You would be surprised how rare that is in this category.
Pager stayed quiet. When something upstream flaked once, the error string told me which parameter to fix without opening logs first.
Students use it for coursework demos. Budget is tight so free tier matters; we coach them to cache aggressively.
Helps prep talking points when retail interest in our name swings after earnings. Not material disclosure, just context for Q&A prep.
Response sizes stay small enough for mobile hotspots. I hate APIs that dump megabytes for a sparkline.
What are you working on?
How will you connect?
Most trend data tools obscure their true cost - per-request models with expiring credits, enterprise tiers requiring annual contracts, free tiers limited to browser usage with no API access. This comparison lays out actual pricing for the most commonly used options in 2026, with specific attention to where costs scale unexpectedly.
pytrends
Price: $0.
Model: Open-source Python library, no commercial product.
What you get: Google Search trend data (relative 0-100), related queries, geographic breakdowns. Weekly or daily data going back 5 years.
Hidden costs: Developer time. pytrends breaks when Google changes its frontend - typically 1-4 times per year. Fixing a broken pipeline or waiting for a community patch has a real time cost. Rate limiting (429 errors) at moderate volumes requires exponential backoff logic and delays. Data is relative-only, so calibration to absolute volume requires additional data sources and engineering.
Rollover: N/A (no credits).
Verdict: Genuinely free, but not free of cost. The engineering overhead and reliability risk have a real price that grows with usage volume and business criticality.
SerpApi
Price:
- $25/month - 1,000 searches/month
- $75/month - 5,000 searches/month
- $150/month - 15,000 searches/month
- $250/month - 30,000 searches/month
Note: "searches" applies across all of SerpApi's endpoints. Google Trends queries use the same credit pool as Google Search, Shopping, etc.
Model: Per-request credits, billed monthly. No rollover - unused credits expire each billing cycle.
What you get: Google Trends data only (interest over time, interest by region, related topics, related queries). Same relative 0-100 data as the native Google Trends interface. No absolute volume. Clean JSON output.
Hidden costs: The no-rollover policy. A team running 500 queries one month and 1,200 the next either overpays on the 500-query month or overages on the 1,200-query month. Variable-volume workflows consistently pay more than the nominal tier cost. The 100-credit free trial requires a credit card and expires - it is not an ongoing free tier.
Effective cost per Google Trends query: ~$0.015 at the $75/month tier, rising to ~$0.025+ for variable-usage teams due to expired credits.
Rollover: None.
Verdict: Reliable and well-maintained. Worth the price for production REST pipelines that need consistent Google Trends JSON. The no-rollover policy significantly raises effective cost for research teams with variable query volumes.
Glimpse
Price:
- Free plan - limited weekly searches (typically 5-10)
- Pro plan - $49/month
- Team plan - $99/month
Model: Subscription. No API access on any public plan as of 2026.
What you get: Browser extension that adds absolute volume overlays to Google Trends. No programmatic access - data is displayed in the browser and can be exported manually from Pro plans.
Hidden costs: Entirely browser-based. No API means no automation - every query is a manual interaction in Chrome. Not usable for pipelines, notebooks, or AI agents.
Rollover: N/A (subscription, not credits).
Verdict: Good value at $49/month for SEO and content teams who live in Google Trends. Zero value for any programmatic or AI-native use case - the lack of API access is a hard constraint.
Exploding Topics
Price:
- Free plan - limited topic browsing
- Entrepreneur - $39/month
- Investor - $99/month
- API access - available on Investor plan and above
Model: Subscription. API access on higher tiers.
What you get: Curated database of trending topics. API on $99+ plans returns data from the curated dataset - no arbitrary keyword queries. Google Search-centric with limited additional sources.
Hidden costs: The curated model means you can only get trends for topics the Exploding Topics editorial team has identified. High-specificity keyword queries (niche products, regional terms, emerging jargon) are unlikely to be in the dataset. API access requires the $99/month Investor plan - the $39/month plan has no programmatic access.
Effective cost per trend data point: $99+/month for API access to a curated set of topics. No per-query pricing.
Rollover: N/A (subscription).
Verdict: Best for trend discovery (finding topics you did not know to search for). Not designed for arbitrary keyword research. API access is expensive relative to what you get if your primary need is querying specific keywords.
Meltwater and Brandwatch
Price: Enterprise contracts, no public pricing. Estimated $15,000-$120,000/year depending on tier and negotiation.
Model: Annual contracts with volume-based licensing. Require sales process.
What you get: Full social media monitoring and trend analytics platforms - news monitoring, social listening, audience analytics, and trend tracking as a component. Meltwater includes Google Search trend proxies; Brandwatch focuses on social signals.
Hidden costs: Annual commitment. Implementation and onboarding time (weeks, not days). These are enterprise platforms, not trend data APIs - the price includes features most users do not need.
Rollover: N/A (annual contract).
Verdict: Appropriate for enterprise media monitoring teams that need the full platform. Significantly overpriced for teams whose primary need is trend data queries.
Trends MCP
Price:
- Free tier - 100 requests/day, permanently, no credit card
- Paid plans - subscription, see trendsmcp.ai for current tiers
Model: Subscription with daily or monthly request allocations. Free tier is permanent, not a trial.
What you get: Live trend data from 15+ sources (Google Search, TikTok, YouTube, Reddit, Amazon, Wikipedia, news, web traffic, app downloads, npm, Steam) via MCP or HTTP. Four tools: get_trends, get_growth, get_ranked_trends, get_top_trends. Absolute volume estimates. Data quality scores.
Hidden costs: None on the free tier. Paid plan pricing is subscription-based, not per-query with expiry.
Effective cost per data point: The get_growth tool with source='all' returns growth metrics across all 15+ platforms in one API call. One request delivers what would require 15+ separate SerpApi-equivalent calls. Effective cost per platform data point is substantially lower than single-source APIs.
Rollover: Free tier resets daily. Paid plan structure is subscription-based.
Verdict: Lowest true cost for multi-platform trend research. The only option with a permanent free tier that includes programmatic API access and MCP integration for AI agents.
Summary
| Tool | Starting price | Free tier | Credit expiry | Sources | API/MCP |
|---|---|---|---|---|---|
| pytrends | $0 | Yes (open-source) | N/A | Google only | Python lib |
| SerpApi | $25/month | Trial (100 credits, expires) | Monthly, no rollover | Google only | REST |
| Glimpse | $49/month | Limited (browser only) | N/A | Google only | None |
| Exploding Topics | $99/month (API) | Browse only | N/A | Primarily Google | REST |
| Meltwater | ~$15k+/year | No | N/A | Multi-platform | Enterprise |
| Brandwatch | ~$40k+/year | No | N/A | Multi-platform | Enterprise |
| Trends MCP | $0 (100 req/day) | Yes, permanent | N/A | 15+ sources | MCP + REST |
Connect
Add to your AI in 30 seconds
An API key is required to connect. Get your free key above, then copy the pre-filled config for your client.
Cursor
Cursor Settings → Tools & MCP → Add a Custom MCP Server
"trends-mcp": { "url": "https://api.trendsmcp.ai/mcp", "transport": "http", "headers": { "Authorization": "Bearer YOUR_API_KEY" } }
+ Add to Cursor
Or paste into Mac / Linux — ~/.cursor/mcp.json
Windows — %USERPROFILE%\.cursor\mcp.json
↑ Get your free key above first — the config won't work without it.
Claude Desktop
User → Settings → Developer → Edit Config — add inside mcpServers
"trends-mcp": { "command": "npx", "args": [ "-y", "mcp-remote", "https://api.trendsmcp.ai/mcp", "--header", "Authorization:${AUTH_HEADER}" ], "env": { "AUTH_HEADER": "Bearer YOUR_API_KEY" } }
Mac — ~/Library/Application Support/Claude/claude_desktop_config.json
Windows — %APPDATA%\Claude\claude_desktop_config.json
Fully quit and restart Claude Desktop after saving.
Claude Code (CLI)
claude mcp add --transport http trends-mcp https://api.trendsmcp.ai/mcp \ --header "Authorization: Bearer YOUR_API_KEY"
Windsurf
Settings → Advanced Settings → Cascade → Add custom server +
"trends-mcp": { "url": "https://api.trendsmcp.ai/mcp", "transport": "http", "headers": { "Authorization": "Bearer YOUR_API_KEY" } }
Mac / Linux — ~/.codeium/windsurf/mcp_config.json
Windows — %USERPROFILE%\.codeium\windsurf\mcp_config.json
Or: Command Palette → Windsurf: Configure MCP Servers
VS Code
Extensions sidebar → search @mcp trends-mcp → Install — or paste manually into .vscode/mcp.json inside servers
"trends-mcp": { "type": "http", "url": "https://api.trendsmcp.ai/mcp", "headers": { "Authorization": "Bearer YOUR_API_KEY" } }
Paste into .vscode/mcp.json, or:
Command Palette (⇧⌘P / Ctrl+Shift+P) → MCP: Add Server
Data Sources
What you can query
All data is normalized to a 0-100 scale for consistent cross-platform comparison.
Tools
What your AI can call
Four tools, organized by how you start. With a keyword, track history and growth. Without one, use discovery to see ranked movers or what is live right now.
You already have a keyword.
Chart how it moves over time and compare growth across sources.
No keyword required.
Ranked lists on one source with a growth sort you choose, or a live snapshot of what is trending across platforms.
Outputs
What you get back
FAQ