# KrystalView

> Use this tool when you need to analyze user behavior, identify UX friction points, and optimize conversion funnels. It connects to the KrystalView analytics platform, allowing you to query visitor sessions, filter by various criteria, and receive detailed session replay data and aggregated site metrics. Ideal for use cases requiring in-depth analysis of user interactions, anomaly detection, and data-driven decision making.

Canonical page: https://skillsregistry.net/skills/krystalview  
JSON: https://api.skillsregistry.net/v1/skills/krystalview

## Description

Connects to the KrystalView analytics platform to query visitor sessions, investigate UX friction points, analyze conversion funnels, and surface anomaly alerts. Supports filtering sessions by country, device type, friction score, and rage clicks, with detailed session replay data including page visits, events, and navigation paths. Provides aggregated site metrics such as bounce rates, average duration, and device breakdowns, along with AI-detected traffic and friction anomalies.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** data-analytics
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/krystalview)
- **Repository:** <https://github.com/krystalview/krystalview-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "krystalview"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/krystalview` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/krystalview/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt