MCP Server Boilerplate
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server Boilerplateshow me how to add a new tool that fetches data from an API"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server Boilerplate
A starter template for building MCP (Model Context Protocol) servers. This boilerplate provides a clean foundation for creating your own MCP server that can integrate with Claude Desktop, Cursor, Claude Code, Gemini, and other MCP-compatible AI assistants.
Purpose
This boilerplate helps you quickly start building:
Custom tools for AI assistants
Resource providers for dynamic content
Prompt templates for common operations
Integration points for external APIs and services
Related MCP server: MCP Server Boilerplate
Features
Two example tools: "hello-world" and "get-mcp-docs"
TypeScript support with ES2022 target and ES modules
Multi-client installation scripts (Claude Desktop, Cursor, Claude Code, Gemini, etc.)
Automatic npm publishing workflow
Environment variable support via
.env.localClean project structure with Zod validation
How It Works
This MCP server template provides:
A basic server setup using the MCP SDK
Example tool implementation
Build and installation scripts
TypeScript configuration for development
The included example demonstrates how to create a simple tool that takes a name parameter and returns a greeting.
Getting Started
Option 1: Use the Published Package (Recommended)
You can use this MCP server directly without cloning:
# Run the server directly with npx
npx @r-mcp/boilerplateOption 2: Customize and Develop
# Clone the boilerplate
git clone <your-repo-url>
cd mcp-server-boilerplate
# Install dependencies
pnpm install
# Build the project
pnpm run build
# Start the server
pnpm startInstallation Scripts
This boilerplate includes convenient installation scripts for different MCP clients:
# Install to all MCP clients (Claude Desktop, Cursor, Claude Code, Gemini, MCP)
pnpm run install-server
# Install to specific clients
pnpm run install-desktop # Claude Desktop
pnpm run install-cursor # Cursor IDE
pnpm run install-code # Claude Code CLI
pnpm run install-code-library # Claude Code Library (~/.claude/mcp-library/)
pnpm run install-mcp # Local .mcp.json for development
# You can also combine multiple targets:
node scripts/update-config.js cursor code desktopThese scripts will:
Build the project automatically (TypeScript compilation + chmod permissions)
Configure clients to use
npx @r-mcp/<directory-name>@latest(auto-updating)Only the local
.mcp.jsonuses the development version (node dist/index.js)Include environment variables from
.env.localif present
Publishing Your Server
To publish your customized MCP server:
# Build, commit, and publish to npm in one command
pnpm run releaseThis script (scripts/build-and-publish.js) will:
Commit any pending changes first
Update package name to
@r-mcp/<directory-name>Update bin name to match directory
Increment patch version automatically
Build the TypeScript project
Commit version bump to git
Push to remote repository
Publish to npm with public access
Usage with MCP Clients
The installation scripts automatically configure your MCP clients. For reference, here's what gets added:
Production Clients (Claude Desktop, Cursor, Claude Code, Gemini):
{
"mcpServers": {
"boilerplate": {
"command": "npx",
"args": ["-y", "@r-mcp/boilerplate@latest"],
"env": {
// Environment variables from .env.local are included here
}
}
}
}Local Development (.mcp.json):
{
"mcpServers": {
"boilerplate": {
"command": "node",
"args": ["/absolute/path/to/dist/index.js"],
"env": {
// Environment variables from .env.local are included here
}
}
}
}After running installation scripts, restart your MCP client to connect to the server.
Customizing Your Server
Adding Tools
Tools are functions that the AI assistant can call. Here's the basic structure:
server.tool(
"tool-name",
"Description of what the tool does",
{
// Zod schema for parameters
param1: z.string().describe("Description of parameter"),
param2: z.number().optional().describe("Optional parameter"),
},
async ({ param1, param2 }) => {
// Your tool logic here
return {
content: [
{
type: "text",
text: "Your response",
},
],
};
}
);Adding Resources
Resources provide dynamic content that the AI can access:
server.resource(
"resource://example/{id}",
"Description of the resource",
async (uri) => {
// Extract parameters from URI
const id = uri.path.split("/").pop();
return {
contents: [
{
uri,
mimeType: "text/plain",
text: `Content for ${id}`,
},
],
};
}
);Adding Prompts
Prompts are reusable templates:
server.prompt(
"prompt-name",
"Description of the prompt",
{
// Parameters for the prompt
topic: z.string().describe("The topic to discuss"),
},
async ({ topic }) => {
return {
description: `A prompt about ${topic}`,
messages: [
{
role: "user",
content: {
type: "text",
text: `Please help me with ${topic}`,
},
},
],
};
}
);Project Structure
├── src/
│ └── index.ts # Main MCP server implementation
├── scripts/
│ ├── update-config.js # Multi-client configuration installer
│ └── build-and-publish.js # Automated npm publishing workflow
├── dist/ # Compiled JavaScript (generated)
├── package.json # Project configuration
├── tsconfig.json # TypeScript configuration
├── CLAUDE.md # Claude Code instructions
├── .env.local # Environment variables (optional)
└── README.md # This fileDevelopment Workflow
Local Development
Make changes to
src/index.tsRun
pnpm run buildto compile TypeScriptTest your server with
pnpm startUse
pnpm run install-mcpfor local testingRestart your MCP client to load changes
Publishing Updates
Test your changes locally
Run
pnpm run releaseto publish to npmClients using
npx @r-mcp/<your-package>@latestauto-updateNo client reconfiguration needed
Environment Variables
Create a .env.local file for environment-specific configuration:
# .env.local
API_KEY=your-api-key
DATABASE_URL=your-database-urlThese variables are automatically included in MCP server configurations during installation.
Next Steps
Fork or clone this boilerplate
Customize the server name and tools in
src/index.tsAdd your own tools, resources, and prompts
Configure environment variables in
.env.localRun
pnpm run releaseto publish your serverInstall to clients with
pnpm run install-server
License
MIT
Available Tools
1 toolmake-html-pageB
Generate an HTML page using GPT-5 and save it to a file path
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'generate[s] an HTML page using GPT-5 and save[s] it to a file path', which implies it performs write operations and uses AI, but lacks details on permissions, error handling, rate limits, or what the 'save' entails (e.g., overwriting files). This is insufficient for a tool with potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality without any wasted words. It directly states the action and outcome, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of generating and saving files with AI, the description is incomplete. It lacks annotations, has no output schema, and doesn't explain behavioral aspects like how the HTML is generated, file path requirements, or error cases. This leaves significant gaps for an AI agent to understand the tool's full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description does not mention any parameters, which is appropriate here since none exist. A baseline of 4 is applied as it correctly avoids redundant information, though it doesn't add value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('generate', 'save') and resources ('HTML page', 'file path'), and mentions the use of 'GPT-5'. However, since there are no sibling tools, the lack of differentiation doesn't reduce the score from the maximum clarity for its standalone purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or constraints. It merely states what the tool does without context for its application, which is a significant gap in usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool 'make-html-page' has a clear, singular purpose that cannot be confused with any other functionality in this set.
The single tool name 'make-html-page' follows a consistent verb-noun pattern, using kebab-case. Since there is only one tool, there is no inconsistency to evaluate, and the naming convention is straightforward and appropriate.
A single tool is too few for a server named 'MCP Server Boilerplate', which implies a broader or more foundational purpose. This minimal set feels thin and underdeveloped for typical boilerplate functionality, which might include multiple utilities or examples.
The tool surface is severely incomplete for a boilerplate server. It only covers generating HTML pages, lacking any other common operations like file management, data processing, or configuration handling that would be expected in a boilerplate context, leading to significant gaps in functionality.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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