rolandtritsch/typescript-mcp-roland
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A simple MCP server implemented in TypeScript to provide information about Roland.
typescript-mcp-roland
A simple Model Context Protocol (MCP) server that provides information about Roland through AI assistant interfaces.
What It Does
This MCP server exposes tools that allow AI assistants (like Claude, ChatGPT, or other MCP-enabled clients) to retrieve information about Roland. When integrated into an AI assistant, it provides a about-roland tool that returns biographical and professional information.
Why This Exists
This server serves as both:
- A functional tool: Provides a standardized way for AI assistants to access information about Roland
- A reference implementation: Demonstrates a minimal, well-structured TypeScript MCP server that can be used as a template for similar projects
Installation
Prerequisites
- Node.js (version 18 or higher recommended)
- An MCP-enabled client (Claude Desktop, Windsurf, or other MCP clients)
Setup
-
Clone the repository:
git clone <repository-url> cd typescript-mcp-roland -
Install dependencies:
npm install -
Build the server:
npm run build -
Update the
serverHomepath insrc/server.ts(line 10) to match your installation location:const serverHome = '/path/to/typescript-mcp-roland'; -
Rebuild after updating the path:
npm run build
Configuration
Add the server to your MCP client configuration. For most clients, add this to your MCP configuration file:
{
"mcpServers": {
"roland": {
"command": "node",
"args": ["/path/to/typescript-mcp-roland/build/server.js"]
}
}
}
Replace /path/to/typescript-mcp-roland with your actual installation path.
For detailed configuration examples, see server.json and mcp_config-template.json.
Usage
Once configured, your AI assistant will have access to the about-roland tool. You can ask questions like:
- "What can you tell me about Roland?"
- "Use the about-roland tool to learn about Roland"
The assistant will retrieve and present the information from the server.
Project Resources
- Implementation Details: See for architecture and implementation documentation
- Contributing: See for development workflow and how to make changes
- MCP Protocol: Learn more at the Model Context Protocol repository
