# askjev

> askjev — pzacca-askjev. Use this tool when you need to interact with Jev, a Typesafe AI, through an unofficial MCP server, allowing you to access its capabilities and integrate with git for version control and collaboration. It solves problems related to AI model management and development, providing a interface for inputs such as code and outputs like model predictions. Ideal for use cases involving AI model training, testing, and deployment in a collaborative environment.

Canonical page: https://skillsregistry.net/skills/pzacca-askjev  
JSON: https://api.skillsregistry.net/v1/skills/pzacca-askjev

## Description

Unofficial MCP server for Jev (Typesafe AI)

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/pZacca/askjev)

## 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": "pzacca-askjev"
    }
  }
}
```

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