mcpField
M
MCP Starter Server

MCP Starter Server

Local
github.com/MatthewDaileyDeveloper Tools14Updated 68w ago

About MCP Starter Server

MCP Starter Server is a minimal TypeScript template for developers building tools for AI assistants. It includes a hello-world tool and a configured build and development workflow.

Key features

  1. 01Example hello-world tool
  2. 02TypeScript and esbuild setup
  3. 03Development tools preconfigured
  4. 04Inspector-based testing

Use cases

  1. 01Start a TypeScript MCP server
  2. 02Try a basic tool implementation
  3. 03Test interactions with Inspector
  4. 04Develop and watch for file changes

MCP support

It is a starter MCP server with a sample `hello_tool` and instructions for connecting it to Claude Desktop. Developers can add tool schemas and implementations.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Starter Server

A minimal ModelContextProtocol server template for building AI assistant tools. This starter provides a basic structure for creating MCP tools that can be used with AI assistants like Claude.

Features

  • Simple "hello world" tool example
  • TypeScript + esbuild setup
  • Development tools preconfigured

Setup to build and run with Claude

  1. Download and install Claude desktop app from claude.ai/download

  2. Clone the repo, install dependencies and build:

npm install
npm run build
  1. Configure Claude to use this MCP server. If this is your first MCP server, in the root of this project run:
echo '{
  "mcpServers": {
    "mcp-starter": {
      "command": "node",
      "args": ["'$PWD'/dist/index.cjs"]
    }
  }
}' > ~/Library/Application\ Support/Claude/claude_desktop_config.json

This should result in an entry in your claude_desktop_config.json like:

"mcpServers": {
  "mcp-starter": {
    "command": "node",
    "args": ["/Users/matt/code/mcp-starter/dist/index.cjs"]
  }
}

If you have existing MCP servers, add the mcp-starter block to your existing config. It's an important detail that the args is the path to <path_to_repo_on_your_machine>/mcp-starter/dist/index.cjs.

  1. Restart Claude Desktop.

  2. Look for the hammer icon with the number of available tools in Claude's interface to confirm the server is running.

  3. If this is all working, you should be able to develop your MCP server using npm run dev and test it in Claude. You'll need to restart Claude each time to restart the MCP server.

Developing with Inspector

For development and debugging purposes, you can use the MCP Inspector tool. The Inspector provides a visual interface for testing and monitoring MCP server interactions.

Visit the Inspector documentation for detailed setup instructions.

To test locally with Inspector:

npm run inspect

To build on file changes run:

npm run watch

Or run both the watcher and inspector:

npm run dev

Publishing

Once you're ready to distribute your server, it's simple!

  1. Set up an NPM account.

  2. Run npm publish. This will publish a package using the project name in package.json

  3. Once published, others can install the server with a config entry like:

"mcpServers": {
  "<your-package-name>": {
    "command": "npx",
    "args": ["<your-package-name>"]
  }
}

Available Tools

The server provides:

  • hello_tool: A simple example tool that takes a name parameter and returns a greeting

Creating New Tools

To add new tools:

  1. Define the tool schema in index.ts
  2. Add it to the tools array in the ListToolsRequestSchema handler
  3. Add the implementation in the CallToolRequestSchema handler

See the hello_tool implementation as an example.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.