B2B market research with live trend data via MCP
B2B market research requires signals that move faster than surveys and annual reports. Trends MCP gives your AI live data from search, LinkedIn, news, Reddit, and web traffic to validate markets, track competitors, and size demand in real time.
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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?
B2B market research is broken when it relies on stale data
Traditional B2B market research depends on analyst reports that are 6-18 months old by the time they are published, surveys that reflect opinions rather than behavior, and traffic tools that require logging into a separate dashboard to export a report.
The problem is not that these sources are wrong. The problem is that they are slow. B2B markets in 2026 move faster than any static research method can track. A new competitor can gain meaningful traction in three months. A product category can shift from niche to mainstream in a single quarter. Survey respondents describe what they did last quarter, not what they are actively searching for today.
Trends MCP solves this by connecting your AI assistant to live data sources directly, so B2B market research happens inside your AI conversation, in real time, across 15+ platforms simultaneously.
What live data sources matter most for B2B research
LinkedIn professional trends
LinkedIn search and engagement data reveals what business professionals are actively discussing, searching for, and engaging with. For B2B markets, this is one of the most direct demand signals available.
Rising LinkedIn trend volume for a keyword like "AI procurement tools" or "supply chain visibility platform" means the professional audience is actively interested in that topic - not passively aware of it. This is the kind of leading indicator that precedes purchasing decisions by weeks to months.
get_trends(keyword='AI procurement', source='linkedin', data_mode='monthly')
Google Search demand for industry keywords
B2B buyers use Google before they engage with any vendor. Search volume for product category keywords ("enterprise HR platform," "B2B payment API," "cloud security compliance") is a direct measure of active buyer consideration at the category level.
Comparing search volume trends over 12-24 months reveals whether a market is growing, peaking, or contracting - without relying on analyst projections.
get_growth(keyword='B2B payment API', percent_growth=['3M', '6M', '1Y'])
News volume for sector coverage
How much media coverage a sector or category is receiving is a reliable indicator of institutional attention. B2B categories that are receiving accelerating news coverage tend to attract more vendor investment, buyer attention, and analyst coverage. News volume is a leading indicator of category legitimacy.
get_trends(keyword='procurement automation', source='news_volume', data_mode='weekly')
Reddit practitioner communities
Many B2B software categories have active Reddit communities: r/sysadmin for IT, r/devops for platform engineering, r/sales for sales technology, r/legaladvice for legal tech, r/accounting for finance tools. Discussion volume in these communities reflects practitioner sentiment, not marketing messaging.
Rising Reddit discussion for a tool category means practitioners are talking about it - asking questions, sharing experiences, comparing alternatives. This is direct product-market evidence.
get_trends(keyword='enterprise data catalog', source='reddit', data_mode='monthly')
Web traffic trends for competitors and category sites
Web traffic growth is one of the most reliable indicators of B2B company traction. A competitor whose site traffic is growing 30% quarter-over-quarter is gaining market presence regardless of what their press releases say. Tracking web traffic trends for key competitors and category-defining websites provides a real-time market share signal.
get_trends(keyword='competitor.com', source='web_traffic', data_mode='monthly')
How to run a B2B market research session with your AI
Once Trends MCP is connected to your AI assistant, a complete B2B market research session looks like this:
1. Validate the category size and trajectory
The AI calls get_growth(keyword='...', percent_growth=['3M', '1Y']) and returns growth rates across sources. This tells you whether you are entering a growing or declining market.
2. Map the competitive landscape
The AI pulls web traffic trend data for each domain and returns a side-by-side comparison. This shows relative competitive momentum without relying on reported metrics.
3. Understand professional buyer interest
LinkedIn data reveals whether the target buyer persona is actively engaging with the category in professional contexts.
4. Check practitioner sentiment
Reddit data shows grassroots practitioner opinion - often the most honest signal about whether a product category is genuinely solving a problem.
5. Monitor news coverage for sector events
News volume data reveals whether the sector is in a period of increased institutional attention that could accelerate buying cycles.
B2B market research use cases
Product category validation
Before committing resources to a new B2B product, validate that the problem is actively being searched for by buyers. Rising Google Search volume for the problem keyword, combined with LinkedIn engagement and Reddit community discussion, provides demand-side evidence that complements customer interviews.
Market entry timing
Entering a B2B market too early means educating buyers at your own expense. Entering too late means competing in a crowded market. Trend velocity - whether search volume is still accelerating or has plateaued - is the most reliable signal for timing decisions.
Competitive displacement analysis
When a competitor is losing momentum (declining web traffic, falling search brand volume, reduced news coverage), the buyers they are losing are going somewhere. Trend data reveals which alternative solutions are gaining the search and traffic that the declining competitor is releasing.
Analyst report validation
Analyst reports describe the market as it was when the research was conducted. Trend data validates whether the analyst's growth projections match current behavioral signals. Significant divergence between analyst projections and live trend data is an important research flag.
Account-based research
For sales and marketing teams doing research on specific target accounts, web traffic trends for a prospect's domain can reveal whether they are growing or contracting - context that changes how a sales conversation should be approached.
Getting started
Get a free API key at trendsmcp.ai - 100 requests per day, no credit card required. Add Trends MCP to your preferred AI client (Claude, Cursor, Windsurf, VS Code, ChatGPT, or others) and run your first B2B market research query in minutes.
Full setup documentation and client-specific configurations are available at trendsmcp.ai.
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