> For the complete documentation index, see [llms.txt](https://perceptdot.gitbook.io/perceptdot/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://perceptdot.gitbook.io/perceptdot/faq.md).

# FAQ

***

## Which AI tools does perceptdot work with?

Any **MCP-compatible** AI tool: Claude Code, Cursor, Windsurf, Cline, and more.\
As long as the tool supports HTTP MCP servers, perceptdot works out of the box.

***

## Do I need to create an account?

No. Just enter your email at [perceptdot.com](https://perceptdot.com) and your API key is sent immediately. No signup, no password.

***

## Where do I put my API key?

Add it to the MCP server URL as a query parameter:

```
https://mcp.perceptdot.com/mcp?api_key=YOUR_KEY
```

See [⚡ Quick Install](/perceptdot/install.md) for tool-specific instructions.

***

## Can I check any website?

Any publicly accessible website works. Pages that require login or are behind a firewall may not be fully analyzed.

***

## What viewports are supported?

Three options: **desktop** (1280px, default), **tablet** (768px), **mobile** (375px).

Tell your AI: *"Check <https://mysite.com> on mobile"* — the agent will use the `viewport` parameter automatically.

***

## Why does it take 5–20 seconds?

Page height determines the number of tiles. A short landing page = 1 tile (\~5s). A long documentation page = multiple tiles (\~20s). Cached results return in under 0.3s.

***

## What is a tile?

perceptdot splits tall pages into 1280×1600px sections (tiles) for analysis.\
Short pages = 1 tile. Long pages = multiple tiles.\
**1 tile = 1 credit.** The scan output always shows how many tiles were analyzed.

***

## Can I use perceptdot in CI/CD without an AI tool?

Yes — use the **GitHub Action**. It runs automatically on every deployment and posts results to your workflow summary.

```yaml
- uses: perceptdot/eye-action@v1
  with:
    url: ${{ steps.deploy.outputs.url }}
    api_key: ${{ secrets.PERCEPT_API_KEY }}
```

See [🤖 GitHub Action](/perceptdot/github-action.md) for the full setup guide.

***

## I'm getting false positives

Sometimes the AI flags intentional design choices as issues. Use `no_cache: true` to re-run, or simply ignore the report if it doesn't match what you see.\
You can also send feedback (`percept_feedback`) to help improve detection accuracy.

***

## I entered my email but didn't receive a key

Visit [perceptdot.com](https://perceptdot.com) and enter your email again — the key will be **resent instantly**. Check your spam folder too.

***

## Something's wrong — where do I get help?

📧 Email us at **<service@perceptdot.com>** — we respond quickly.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://perceptdot.gitbook.io/perceptdot/faq.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.