# Introduction

CosmetiQ-MCP lets you leverage your favourite AI platforms – such as Claude, ChatGPT, and Cursor – to explore a rich cosmetics data ecosystem featuring products, ingredients, and consumer feedback.

## Key Features

* **MCP-native connectivity** – CosmetiQ-MCP leverages Model Context Protocol, so that compliant Large Language Model - LLM (e.g., Claude Sonnet 4) or AI Agent framework can plug straight into vertical cosmetics data without custom wrappers.
* **Unified cosmetics knowledge** – A clean large dataset that seamlessly tie *consumer feedbacks (e.g., about texture and fragrance)* to *products* and *ingredients*, empowering marketing and R\&D teams with actionable insights.
* **Effective Tools & Prompts** – Pre-built functions and prompt templates let LLMs and AI Agents tap the dataset effortlessly, turning day-to-day cosmetic tasks into single-command workflows.

## Getting Started

1. **Create an account** at [**www.cosmetiqmcp.simulation.bio**](http://www.cosmetiqmcp.simulation.bio)
2. **Generate a token** in your dashboard
3. **Replace the token** into `YOUR_TOKEN_HERE` section as shown below:

   ```json
   {
     "mcpServers": {
       "cosmetiq-mcp": {
         "command": "npx",
         "args": [
           "-y",
           "mcp-remote",
           "--header",
           "Authorization: Bearer YOUR_TOKEN_HERE"
         ]
       }
     }
   }
   ```
4. **Copy and paste the text with the token** into `config.json` file of your AI Host.

## Next Steps

* Follow our [Quickstart](/getting-started/quickstart.md) guide to query CosmetiQ's dataset
* Explore our comprehensive guides on:
  * [Guided Examples](/guided-examples/innovation-and-r-and-d-teams.md)
  * [Data](/data/overview.md)
  * [Subscription](/subscription/premium-plan.md)

## Contact Us

Need help or have questions? Reach out to us:

* Email : **<info@icarex.ai>**


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://cosmetiqmcp-docs.simulation.bio/getting-started/introduction.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.