# Midnight + Next.js

> Use this tool when you need to build, deploy, and manage decentralized applications on the Midnight Network blockchain. It solves problems related to smart contract development, wallet management, and network querying, providing features like compilation, deployment, and analysis. Ideal for use cases involving Compact contracts, tDUST tokens, and decentralized application development with Next.js.

Canonical page: https://skillsregistry.net/skills/fractionestate-midnight-nextjs  
JSON: https://api.skillsregistry.net/v1/skills/fractionestate-midnight-nextjs

## Description

Provides development tools for Midnight Network blockchain applications. Includes smart contract compilation, deployment, and analysis for Compact contracts, wallet management for tDUST tokens, network querying, and documentation search. Also integrates Next.js DevTools for building decentralized applications with features like browser automation and dev server discovery.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/fractionestate-midnight-nextjs)
- **Repository:** <https://github.com/dajo-code/midnight-nextjs-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": "fractionestate-midnight-nextjs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fractionestate-midnight-nextjs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fractionestate-midnight-nextjs/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