# kaizen-lab

> Use this tool when you need to validate product hypotheses and run lean startup cycles, as it solves problems related to product-market fit and customer discovery through its core workflows and AI-native platform. It takes in inputs such as product hypotheses, experiment results, and customer research, and outputs validated learnings, prioritized roadmaps, and product-market fit scores. Use KaizenLab in the context of product development and iteration to streamline your workflow and make data-driven decisions.

Canonical page: https://skillsregistry.net/skills/toshipon-kaizen-lab  
JSON: https://api.skillsregistry.net/v1/skills/toshipon-kaizen-lab

## Description

KaizenLab is an AI-native hypothesis validation platform for product teams running lean startup cycles.

Connect your AI agent (Claude, Cursor, etc.) to access 56 MCP tools covering the full PMF validation workflow:

**Core workflows:**
- 🧪 Hypothesis Canvas — create, update, and iterate on product hypotheses with sticky notes per field
- ✅ Verification Canvas — plan experiments, run them, validate or invalidate results
- 💡 Learnings — add, search, and analyze patterns across all learnings with AI
- 👥 Personas & Interviews — customer research and discovery
- 🗺️ Roadmap — prioritize next actions from validated learnings
- 📊 PMF Score — track product-market fit progress across 5 categories

**Expert mode:**
Use the MCP directly from Claude Code, Cursor, or any MCP-compatible client to run hypothesis validation loops entirely through your AI agent — no UI required.

Generate your API key at https://kaizen-lab.buildgeeks.dev/settings

## 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:** ai-ml
- **Updated:** 2026-05-12

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/toshipon/kaizen-lab)

## 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": "toshipon-kaizen-lab"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/toshipon-kaizen-lab` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/toshipon-kaizen-lab/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