# moss-soundeffect

> moss-soundeffect — vladimirtalyzin-moss-soundeffect-v2-0-mps-rocm. Use this tool when you need to generate custom sound effects from text inputs, solving the problem of limited audio resources for applications like multimedia presentations or interactive experiences. It takes text descriptions as input and produces locally generated sound effects as output, leveraging a diffusion model for high-quality audio. Ideal for use cases where dynamic audio generation is required, such as game development or virtual reality applications.

Canonical page: https://skillsregistry.net/skills/vladimirtalyzin-moss-soundeffect-v2-0-mps-rocm  
JSON: https://api.skillsregistry.net/v1/skills/vladimirtalyzin-moss-soundeffect-v2-0-mps-rocm

## Description

Exposes text-to-audio sound effect generation as an MCP tool, allowing clients like Claude Desktop to generate sound effects locally using a diffusion model, with support for AMD ROCm and Apple Silicon.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/g3iham6mlb)
- **Repository:** <https://github.com/VladimirTalyzin/MOSS-SoundEffect_v2.0_MPS_ROCm>

## 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": "vladimirtalyzin-moss-soundeffect-v2-0-mps-rocm"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vladimirtalyzin-moss-soundeffect-v2-0-mps-rocm` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vladimirtalyzin-moss-soundeffect-v2-0-mps-rocm/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