# Rapidly

> Rapidly — co-rapidly-rapidly. Use this tool when you need to validate assumptions and test ideas before investing in implementation, to solve problems of unnecessary development and resource waste. It helps coordinate experiments across your portfolio, streamlining the innovation process. By providing a platform for experimentation, Rapidly takes in ideas and hypotheses as inputs and outputs actionable insights and data-driven recommendations.

Canonical page: https://skillsregistry.net/skills/co-rapidly-rapidly  
JSON: https://api.skillsregistry.net/v1/skills/co-rapidly-rapidly

## Description

Test the idea before you build it. Rapidly works inside your AI agent.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/co.rapidly%2Frapidly)
- **Repository:** <https://github.com/Exponentially-Platform/Rapidly-MCP>

## Use it

MCP endpoint published by the skill: `https://www.rapidly.co/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": "co-rapidly-rapidly"
    }
  }
}
```

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