https://github.com/jcasare/mcp-craft
Scaffold, test, and register MCP servers across Claude, Cursor, VS Code, Codex, and Gemini
https://github.com/jcasare/mcp-craft
ai-tools claude cli developer-tools mcp mcp-server model-context-protocol scaffold typescript
Last synced: 3 months ago
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Scaffold, test, and register MCP servers across Claude, Cursor, VS Code, Codex, and Gemini
- Host: GitHub
- URL: https://github.com/jcasare/mcp-craft
- Owner: jcasare
- License: mit
- Created: 2026-03-08T18:17:46.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2026-03-08T18:27:14.000Z (4 months ago)
- Last Synced: 2026-03-08T22:36:46.434Z (4 months ago)
- Topics: ai-tools, claude, cli, developer-tools, mcp, mcp-server, model-context-protocol, scaffold, typescript
- Language: TypeScript
- Size: 102 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-mcp-devtools - jcasare/mcp-craft - CLI toolkit for scaffolding, testing, and registering MCP servers across Claude, Cursor, VS Code, Codex, and Gemini (Frameworks / Common Lisp)
- awesome-mcp-devtools - jcasare/mcp-craft - CLI toolkit for scaffolding, testing, and registering MCP servers across Claude, Cursor, VS Code, Codex, and Gemini (Frameworks / Common Lisp)
README
# mcp-craft
[](https://www.npmjs.com/package/mcp-craft)
[](LICENSE)
CLI toolkit for scaffolding, testing, and managing [MCP (Model Context Protocol)](https://modelcontextprotocol.io) servers.
Build MCP servers in seconds, not hours.
## What is MCP?
MCP is like a **USB port for AI apps**. It's an open protocol that lets AI applications (Claude, Cursor, VS Code Copilot, Gemini, Codex) connect to external tools and data sources through a standard interface.
You build a server once, and any MCP-compatible AI app can use it.
| Primitive | What it is | Example |
| ------------- | -------------------------------- | ------------------------------------------------- |
| **Tools** | Functions the AI can call | `get_weather`, `search_database`, `send_email` |
| **Resources** | Data the AI can read | Files, DB records, API responses |
| **Prompts** | Reusable message templates | `code_review`, `summarize`, `translate` |
## Installation
```bash
npm install -g mcp-craft
```
Or use without installing:
```bash
npx mcp-craft init my-server
```
## Quick Start
```bash
# 1. Scaffold a new MCP server
mcp-craft init my-server
# 2. Install dependencies and build
cd my-server
npm install
npm run build
# 3. Add more capabilities
mcp-craft add tool search_docs
mcp-craft add resource config
# 4. Test your server
mcp-craft test
# 5. Register with your AI clients
mcp-craft register
```
## Commands
### `mcp-craft init [name]`
Interactively scaffold a new MCP server project. Asks you for:
- Project name and description
- Transport type (stdio or HTTP)
- Which primitives to include (tools, resources, prompts)
Generates a complete, ready-to-build TypeScript project with example code.
### `mcp-craft add `
Add a new tool, resource, or prompt to an existing MCP server project.
```bash
mcp-craft add tool get_weather # Add a tool
mcp-craft add resource user_data # Add a resource
mcp-craft add prompt code_review # Add a prompt
```
### `mcp-craft test`
Validate your MCP server:
1. Builds the project (`npm run build`)
2. Spawns the server as a subprocess
3. Sends JSON-RPC `initialize` request
4. Lists all tools, resources, and prompts
5. Reports pass/fail with details
### `mcp-craft inspect`
Launch the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) — a visual browser-based tool for testing your server interactively.
### `mcp-craft register`
Register your MCP server with installed AI clients. Detects which clients are installed and updates their config files (or runs their CLI commands).
## Supported AI Clients
| Client | Method | Config Location |
| -------------- | ----------------------- | ------------------------------------------------------------------ |
| Claude Desktop | Config file | `~/Library/Application Support/Claude/claude_desktop_config.json` |
| Claude Code | CLI (`claude mcp add`) | `~/.claude/settings.json` |
| Cursor | Config file | `~/.cursor/mcp.json` |
| Windsurf | Config file | `~/.windsurf/mcp.json` |
| VS Code | Config file | `.vscode/mcp.json` |
| Codex (OpenAI) | CLI (`codex mcp add`) | `~/.codex/config.toml` |
| Gemini CLI | CLI (`gemini mcp add`) | `~/.gemini/settings.json` |
## Generated Project Structure
```text
my-server/
├── src/
│ └── index.ts # Server entry point with tools/resources/prompts
├── build/ # Compiled output (gitignored)
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript config
└── README.md # Auto-generated docs
```
## Contributing
Contributions are welcome! Please feel free to submit a pull request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/my-feature`)
3. Commit your changes (`git commit -m 'Add my feature'`)
4. Push to the branch (`git push origin feature/my-feature`)
5. Open a Pull Request
## License
[MIT](LICENSE)