# Streamfog MCP

> Use this tool when you need to enhance live streams with interactive AR effects, face filters, and Vtuber avatars, and control them seamlessly through MCP tools. It solves the problem of manual AR lens management by automating the process through AI-driven orchestration. It takes in live OBS streams as input and outputs controlled AR effects via the local Streamer.bot WebSocket bridge.

Canonical page: https://skillsregistry.net/skills/sandraschi-streamfog-mcp  
JSON: https://api.skillsregistry.net/v1/skills/sandraschi-streamfog-mcp

## Description

AI-driven AR lens orchestrator for live OBS streams that enables control of Streamfog face filters, AR effects, and Vtuber avatars through MCP tools via the local Streamer.bot WebSocket bridge.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-05-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/urapy7xk6x)
- **Repository:** <https://github.com/sandraschi/streamfog-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": "sandraschi-streamfog-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sandraschi-streamfog-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sandraschi-streamfog-mcp/pull`

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