AI Visibility API: track how brands appear in AI answers.

An API that returns structured data on how a brand appears in answers from AI models such as ChatGPT, Claude, Gemini and Perplexity. It is one of my own projects, built through LLM Scout, which I founded.

View the repository on GitHub Read the API documentation

What it is

The AI Visibility API is the public repository for the LLM Scout Brand Intelligence API. The API lets developers, agencies and software platforms monitor how brands appear in answers from AI models. The repository holds the documentation, integration guides and code examples.

A disclosure: this is my own project. I founded LLM Scout, which runs the API. So I have a commercial interest in it. The repository is open source under the MIT licence. The API itself is a service run by LLM Scout. Using it needs a key.

What you can build with it

Brand monitoring: Track whether a brand appears in answers from AI models and how often.
Competitor tracking: See which competing brands are named in AI answers and how visible each one is.
Citation tracking: List the domains that AI models cite when they recommend a brand.
Dashboards: Put AI visibility data into a client report or an internal dashboard.

How it works

One request goes in and structured data comes back. You send a brand name and your API key to a single endpoint, with an optional language code. The API replies in JSON.

GET https://llmscout.co/api/brand-intelligence

import requests

response = requests.get(
    "https://llmscout.co/api/brand-intelligence",
    params={"brand": "Stripe", "api_key": "YOUR_API_KEY"}
)

data = response.json()
print(f"Visibility Score: {data['visibility_score']}%")
print(f"Share of Voice: {data['share_of_voice']}%")
print(f"Competitors: {[c['name'] for c in data['competitors'][:5]]}")

The Python quick-start example from the repository. Replace YOUR_API_KEY with your own key. The repository has the same request in cURL and JavaScript.

What comes back

visibility_score: The percentage of AI queries in which the brand appears.
share_of_voice: The brand's share of all mentions, set against its competitors.
competitors: Competing brands, each with its own visibility score.
related_prompts: The prompts that surface the brand in AI answers, with results for each platform.
platform_coverage: A breakdown by AI platform.
google_trends: Search interest over time.
citations: The domains AI models cite when they recommend the brand.

API keys are issued through the LLM Scout API portal. The full reference is in the API documentation.

Workflow integrations

This site is about integrating AI into the way a business already works. This is the part of the project closest to that. The repository includes three ready-made integrations, so the data can be sent to the tools a team already uses.

n8n: An importable workflow for automated brand monitoring.
Make.com: A scenario for monitoring AI visibility without writing code.
Claude, via MCP: A Model Context Protocol server, so the API can be used as a tool inside Claude Desktop.

Where to go next

AI strategy / Implementation / Training