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 Boilerplate show me how to add a new tool to my MCP server"
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.
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, Cursor, or other MCP-compatible AI assistants.
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: JSON MCP Boilerplate
Simple "hello-world" tool example
TypeScript support with proper type definitions
Easy installation scripts for different MCP clients
Clean project structure ready for customization
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.
# 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 startThis boilerplate includes convenient installation scripts for different MCP clients:
# For Claude Desktop
pnpm run install-desktop
# For Cursor
pnpm run install-cursor
# For Claude Code
pnpm run install-code
# Generic installation
pnpm run install-serverThese scripts will build the project and automatically update the appropriate configuration files.
The installation script will automatically add the configuration, but you can also manually add it to your claude_desktop_config.json file:
{
"mcpServers": {
"your-server-name": {
"command": "node",
"args": ["/path/to/your/dist/index.js"]
}
}
}Then restart Claude Desktop to connect to the server.
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",
},
],
};
}
);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}`,
},
],
};
}
);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}`,
},
},
],
};
}
);├── src/
│ └── index.ts # Main server implementation
├── scripts/ # Installation and utility scripts
├── dist/ # Compiled JavaScript (generated)
├── package.json # Project configuration
├── tsconfig.json # TypeScript configuration
└── README.md # This fileMake changes to src/index.ts
Run pnpm run build to compile
Test your server with pnpm start
Use the installation scripts to update your MCP client configuration
Update package.json with your project details
Customize the server name and tools in src/index.ts
Add your own tools, resources, and prompts
Integrate with external APIs or databases as needed
MIT
Make an MCP server
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | The name of the MCP server |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Make an MCP server' suggests a creation/write operation, but the description doesn't clarify whether this is a read, write, or configuration operation, nor does it mention any side effects, permissions needed, or response format.
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?
While the description is brief (3 words), this is under-specification rather than effective conciseness. The single sentence doesn't earn its place by providing meaningful information beyond the tool name.
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 no annotations, no output schema, and a description that fails to explain what the tool does or how to use it, this is completely inadequate. The description doesn't compensate for the lack of structured information about this tool's behavior and purpose.
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?
Schema description coverage is 100% (the single parameter 'name' has a clear description in the schema), so the baseline is 3. The tool description adds no additional parameter information beyond what's already documented in the input 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 'Make an MCP server' is a tautology that essentially restates the tool name 'get-mcp-docs' without clarifying what the tool actually does. It doesn't specify what resource is being accessed or what operation is performed, and it doesn't distinguish this tool from its sibling 'hello-world'.
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. There's no mention of context, prerequisites, or comparison to the sibling tool 'hello-world', leaving the agent with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Say hello to the user
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | The name of the user |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Say hello to the user' implies a simple, read-only output operation, but it doesn't specify what the tool returns (e.g., a greeting string), any side effects, or error handling. This is a significant gap for a tool with no structured behavioral hints.
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 ('Say hello to the user') that directly states the purpose without any waste. It's appropriately sized for a simple tool and front-loaded with the core action.
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 tool's simplicity (1 parameter, no annotations, no output schema), the description is incomplete. It doesn't explain what the tool returns (e.g., a formatted greeting), which is critical since there's no output schema. For a basic tool, more context on behavior and output is needed to be fully helpful.
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 description doesn't mention parameters, but the input schema has 100% coverage with a clear description for the single parameter 'name'. Since schema_description_coverage is high (>80%), the baseline is 3. The description doesn't add meaning beyond the schema, but it doesn't need to compensate for low coverage.
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 'Say hello to the user' clearly states the tool's purpose with a specific verb ('say') and target ('hello to the user'). It's not tautological with the name 'hello-world', which is more generic. However, it doesn't explicitly differentiate from the sibling tool 'get-mcp-docs', which appears unrelated, so it doesn't reach the highest score.
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. It doesn't mention any context, prerequisites, or exclusions. With a sibling tool 'get-mcp-docs' that seems unrelated, there's no explicit or implied comparison, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
get-mcp-docshello-worldThe two tools have completely distinct purposes: 'get-mcp-docs' is for server creation/development, while 'hello-world' is for user interaction/greeting. There is no overlap or ambiguity in their functions.
The naming is inconsistent: 'get-mcp-docs' uses kebab-case with a verb-object structure, while 'hello-world' uses kebab-case but is a noun-phrase without a clear action verb. This mixing of conventions reduces predictability.
With only 2 tools, this server feels too thin for a 'boilerplate' purpose, which typically implies foundational or example functionality. The count is insufficient to demonstrate meaningful coverage or utility.
For a boilerplate server, there are significant gaps: no tools for configuration, testing, deployment, or common MCP operations like listing resources. The surface is severely incomplete for development or example use cases.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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