# swarmrails

> Use this tool when you need to access and leverage various Bittensor subnets, such as text, image, and video analysis, without requiring node setup or TAO. It provides a free-to-try interface for calling multiple AI models, including TTS, forecasting, and prediction markets. Ideal for use cases involving multi-model integration and AI-driven insights, swarmrails simplifies the process of tapping into diverse AI capabilities.

Canonical page: https://skillsregistry.net/skills/wizerai-swarmrails  
JSON: https://api.skillsregistry.net/v1/skills/wizerai-swarmrails

## Description

Call any Bittensor subnet from Claude — text, image, video, code, TTS, forecasting, 3D assets, and prediction market intelligence. No TAO, no node setup, free to try.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-05-13

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/wizerai/swarmrails)

## 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": "wizerai-swarmrails"
    }
  }
}
```

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