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 custom 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?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Make an MCP server' suggests a creation/write operation, but the description doesn't clarify what this action entails, whether it requires specific permissions, what happens if a server with that name already exists, or what the expected outcome is. No behavioral traits are disclosed beyond the vague verb 'make'.
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 extremely concise at just three words, but this brevity comes at the cost of meaningful information. While it's not verbose or repetitive, it's under-specified rather than efficiently informative. The single sentence doesn't waste words but fails to provide necessary context.
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 has no annotations, no output schema, and a vague description, the description is insufficiently complete. For a tool that appears to perform some kind of creation operation (based on the verb 'make'), the description should explain what gets created, what the result looks like, and any important constraints. The current description leaves too many unanswered questions about the tool's behavior and outcomes.
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 100% description coverage, with the single parameter 'name' clearly documented as 'The name of the MCP server.' The description adds no additional parameter information beyond what the schema provides. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.
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' in different words. It doesn't specify what 'make' means in this context (create? generate? fetch?), nor does it clarify what 'MCP server' refers to. The description fails to distinguish this tool from its sibling 'hello-world' or explain what resource it operates on.
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 prerequisites, appropriate contexts, or comparison with the sibling 'hello-world' tool. Users are left with no information about when this tool should be selected over other options.
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. 'Say hello to the user' suggests a read-only, non-destructive operation, but it doesn't disclose any behavioral traits like whether it requires authentication, has rate limits, or what format the greeting takes. The description is too minimal to provide meaningful behavioral context.
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 extremely concise at just four words, with zero wasted language. It's front-loaded with the core purpose and appropriately sized for a simple tool.
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 'say hello' actually does (e.g., returns a greeting message), leaving the agent to guess about the tool's behavior and output. For even a simple tool, more context would be 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 schema description coverage is 100%, with the single parameter 'name' documented as 'The name of the user'. The description doesn't add any parameter semantics beyond what the schema provides, so it meets the baseline of 3 for high schema 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 hello') and target ('user'), but it's somewhat vague about what exactly 'say hello' entails. It doesn't distinguish from the sibling tool 'get-mcp-docs', though that's understandable given their different domains.
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?
No guidance is provided on when to use this tool versus alternatives or in what context it's appropriate. The description implies it's for greeting users, but doesn't specify scenarios, prerequisites, or exclusions.
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.
v1.0.0get-mcp-docs2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falsehello-world2 fields changedInput schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falseget-mcp-docshello-worldThe two tools have completely distinct purposes: one is for creating MCP servers (get-mcp-docs) and the other is for greeting users (hello-world). There is no overlap or ambiguity between them, making it easy for an agent to select the correct tool.
The naming is inconsistent: get-mcp-docs uses kebab-case with a verb-noun structure, while hello-world uses kebab-case but is a phrase rather than a clear verb-noun pattern. This mixed style reduces predictability and readability.
With only 2 tools, this server feels too thin for a boilerplate purpose, which typically implies a foundational set of utilities. The scope seems limited, lacking coverage for common operations like setup, configuration, or testing that might be expected in a boilerplate.
Inferred domain is MCP server development, but the tool surface is severely incomplete: it includes a documentation tool and a greeting, but misses essential CRUD/lifecycle operations (e.g., initialize, configure, deploy, test). This will likely cause agent failures in practical workflows.
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If you are the server author, to access and configure the admin panel.
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