# RFix

> Use this tool when you need to generate and analyze RF signal projects from textual prompts, creating visualizations through graph inspection and exporting IQ data for further processing. It solves problems related to RF signal design, testing, and optimization, providing a streamlined workflow for signal creation and analysis. Ideal for use cases involving custom signal generation, signal processing, and data export for applications such as telecommunications, radar, and wireless communication systems.

Canonical page: https://skillsregistry.net/skills/ai-rfix-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ai-rfix-mcp

## Description

Create RF signal projects from prompts, inspect graphs, and export IQ data.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-06-12

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.rfix%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mcp.rfix.ai/mcp`

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": "ai-rfix-mcp"
    }
  }
}
```

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