# Vantage

> Use this tool when you need to organize and recall insights from across the web, saving time and reducing information loss. Vantage solves the problem of fragmented knowledge by creating a shared memory layer, allowing you to capture and query signals with filters and full-text search. It is ideal for users who need to track and analyze information from multiple sources, providing a unified interface for strategic analysis and decision-making.

Canonical page: https://skillsregistry.net/skills/cavendo-vantage  
JSON: https://api.skillsregistry.net/v1/skills/cavendo-vantage

## Description

Vantage creates a shared memory layer across Claude, Cursor, and other MCP-compatible clients, enabling you to save signals from what you see across the web and query them later. Instead of losing insights across tabs, screenshots, and notes, you capture them once and access them anywhere. The system provides full-text search with filters for platform, topic, date range, and importance, along with source tracking and business context integration for strategic analysis.

## Trust

- **Trust score (0–1):** 0.36
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

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

## Source

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

## 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": "cavendo-vantage"
    }
  }
}
```

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