Get AI Visibility DataAcross ChatGPT, Claude, Gemini & Perplexity with one API call
Query 4 LLM APIs (ChatGPT, Claude, Gemini, Perplexity) in parallel. Plus real-time Perplexity UI scraping for ground truth. One bearer token, one response shape.
300 free credits · No card required · Subscribe when you need more
# Query 4 answer engines in one call curl https://api.mentionsapi.com/v1/ask \ -H "Authorization: Bearer $MENTIONSAPI_KEY" \ -H "Content-Type: application/json" \ -d '{ "providers": ["openai", "anthropic", "gemini", "perplexity"], "prompt": "What are the best project management tools in 2026?", "track_brands": ["Notion", "Linear", "Asana"] }'
Everything you need to ship an AI-visibility feature.
Each one is the thing you'd normally have to write yourself. We did it once, so you don't.
One API, four answer engines
Query GPT-5, Claude 4, Gemini 2.5, and Perplexity Sonar through a single endpoint. One bearer token, one rate limit, one response shape. Swap providers by editing an array.
providers: ["openai", "anthropic", "gemini", "perplexity"]
Brand tracking built in
Pass a track_brands array and get back position, sentiment, surrounding context, and every cited URL per mention. No regex, no custom parser, just a clean array your dashboard can render.
{ brand: "Notion",
rank: 1,
sentiment: "positive" }Cached and rate-limit-safe
Instant low-cost answers for recently-asked queries, automatic retries, per-key rate limits, and partial-success fallbacks when a provider degrades. Your monitoring dashboard never takes down a provider outage with it.
// automatic retries + cache x-cache: "HIT" x-cache-tier: "shared"
From zero to structured brand data in three steps.
No SDK to install. No parser to write. A bearer token and a JSON body is the whole integration.
- STEP 01
Authenticate with a bearer token
Create an API key in the dashboard. One key, one
Authorizationheader. Good across every provider we support.bashcurl https://api.mentionsapi.com/v1/ask \ -H "Authorization: Bearer lvk_live_xxxxxxxxxxxxxxxx"
- STEP 02
POST a prompt with providers and brands
One request fans out to every provider you list, in parallel. Pass
track_brandsto get structured mentions back.POST /v1/ask{ "providers": ["openai", "anthropic", "gemini", "perplexity"], "prompt": "What are the top CRMs for startups?", "track_brands": ["HubSpot", "Salesforce", "Attio"] } - STEP 03
Read structured mentions and citations
Every provider returns the same shape. Loop through results; render mentions by rank, sentiment, or competitor cohort.
JavaScriptfor (const m of data.brand_mentions) { console.log(m.provider, m.brand, "#" + m.rank, m.sentiment); } // openai HubSpot #1 positive // openai Attio #2 positive // anthropic Attio #1 positive
Built for teams shipping AI-visibility tools in 2026.
Four common shapes. Same API underneath. Start free, upgrade when your product ships.
Add AI visibility to your client reports
Show clients exactly how ChatGPT, Claude, Gemini, and Perplexity describe them vs. their competitors, in the same report where you deliver SERP rankings.
AI visibility APISkip the data-layer sprint
Ship your GEO product with a dashboard and a storyline, not four SDKs and a normalization layer. Bulk prompt runs, webhooks, and historical replay included.
GEO APIPipe structured mentions into your warehouse
JSON in, JSON out. Webhook deliveries land in your bucket on a schedule; scheduled queries roll into Snowflake/BigQuery without a glue layer.
Brand monitoring APIExperiment with four LLMs in one call
Compare outputs side-by-side without wiring four SDKs. Cache is shared across customers so R&D queries stay cheap. Swap providers by editing an array.
Multi-LLM APISimple plans. Credits do the metering.
Subscribe from $5/month and every call debits credits by what it actually runs. Repeat checks cost a handful of credits; premium 4-provider fan-outs are 250.
The shape of feedback we keep hearing.
We're in public beta. Quotes below are paraphrased from early users with their details anonymized on request. Email us to talk to a reference.
We dropped three SDKs and a normalization layer in the same PR we rolled MentionsAPI out. The biggest surprise was how accurate the sentiment tagging is. We stopped second-guessing it after the first week.
We were polling four providers daily for 20 clients. After we switched, cache hits did what we hoped: same freshness, roughly a quarter of the bill. Our client dashboards didn't notice a difference.
I wired an internal brand-watch tool in a weekend. The structured mention object (position, sentiment, cited URL) is the specific shape I'd have built myself after getting tired of regex.
Frequently asked questions
Full details on the pricing and methodology pages. Anything else, email [email protected] — we answer fast.
Ship your AI-visibility feature this week.
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