smrtm-mcp
Click on "Deploy 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., "@smrtm-mcpCreate a new prompt template for summarizing meeting notes"
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.
xmcp Application
This project was created with create-xmcp-app.
Getting Started
First, run the development server:
npm run dev
# or
yarn dev
# or
pnpm devThis will start the MCP server with the selected transport method.
Related MCP server: easy-mcp
Project Structure
This project uses the structured approach where tools, prompts, and resources are automatically discovered from their respective directories:
src/tools- Tool definitionssrc/prompts- Prompt templatessrc/resources- Resource handlers
Tools
Each tool is defined in its own file with the following structure:
import { z } from 'zod'
import { type InferSchema, type ToolMetadata } from 'xmcp'
export const schema = {
name: z.string().describe('The name of the user to greet'),
}
export const metadata: ToolMetadata = {
name: 'greet',
description: 'Greet the user',
annotations: {
title: 'Greet the user',
readOnlyHint: true,
destructiveHint: false,
idempotentHint: true,
},
}
export default function greet({ name }: InferSchema<typeof schema>) {
return `Hello, ${name}!`
}Prompts
Prompts are template definitions for AI interactions:
import { z } from 'zod'
import { type InferSchema, type PromptMetadata } from 'xmcp'
export const schema = {
code: z.string().describe('The code to review'),
}
export const metadata: PromptMetadata = {
name: 'review-code',
title: 'Review Code',
description: 'Review code for best practices and potential issues',
role: 'user',
}
export default function reviewCode({ code }: InferSchema<typeof schema>) {
return `Please review this code: ${code}`
}Resources
Resources provide data or content with URI-based access:
import { z } from 'zod'
import { type ResourceMetadata, type InferSchema } from 'xmcp'
export const schema = {
userId: z.string().describe('The ID of the user'),
}
export const metadata: ResourceMetadata = {
name: 'user-profile',
title: 'User Profile',
description: 'User profile information',
}
export default function handler({ userId }: InferSchema<typeof schema>) {
return `Profile data for user ${userId}`
}Adding New Components
Adding New Tools
To add a new tool:
Create a new
.tsfile in thesrc/toolsdirectoryExport a
schemaobject defining the tool parameters using ZodExport a
metadataobject with tool informationExport a default function that implements the tool logic
Adding New Prompts
To add a new prompt:
Create a new
.tsfile in thesrc/promptsdirectoryExport a
schemaobject defining the prompt parameters using ZodExport a
metadataobject with prompt information and roleExport a default function that returns the prompt text
Adding New Resources
To add a new resource:
Create a new
.tsfile in thesrc/resourcesdirectoryUse folder structure to define the URI (e.g.,
(users)/[userId]/profile.ts→users://{userId}/profile)Export a
schemaobject for dynamic parameters (optional for static resources)Export a
metadataobject with resource informationExport a default function that returns the resource content
Building for Production
To build your project for production:
pnpm buildThis will compile your TypeScript code and output it to the dist directory.
Running the Server
You can run the server for the transport built with:
HTTP:
node dist/http.jsSTDIO:
node dist/stdio.js
Given the selected transport method, you will have a custom start script added to the package.json file.
For HTTP:
pnpm start-httpFor STDIO:
pnpm start-stdioLearn More
This server cannot be deployed
Maintenance
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