# xavier

> xavier — iberi22-xavier. Use this tool when you need to efficiently manage vector memory and knowledge graphs for AI agents, solving problems related to communal context and data storage. It provides a robust interface through HTTP, CLI, and MCP, allowing for seamless integration with various applications. Ideal for use cases requiring scalable and organized data management, such as powering communal context platforms like SWAL.

Canonical page: https://skillsregistry.net/skills/iberi22-xavier  
JSON: https://api.skillsregistry.net/v1/skills/iberi22-xavier

## Description

Xavier — Rust vector memory & knowledge graph for AI agents (HTTP/CLI/MCP). Powers SWAL communal context

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/iberi22/xavier)

## 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": "iberi22-xavier"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/iberi22-xavier` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/iberi22-xavier/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
