Siratul804/MCP-Server-Node.js
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The Model Context Protocol (MCP) allows you to build servers that expose data and functionality to LLM applications in a secure, standardized way.
MCP TypeScript Server With Node.js
What is MCP?
The Model Context Protocol (MCP) lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. Think of it like a web API, but specifically designed for LLM interactions. MCP servers can:
- Expose data through resources (think of these sort of like GET endpoints; they are used to load information into the LLM's context)
- Provide functionality through tools (sort of like POST endpoints; they are used to execute code or otherwise produce a side effect)
- Define interaction patterns through prompts (reusable templates for LLM interactions)
- And more!
Resources
Resources are how you expose data to LLMs. They're similar to GET endpoints in a REST API - they provide data but shouldn't perform significant computation or have side effects:
// Static resource
server.resource(
"config",
"config://app",
async (uri) => ({
contents: [{
uri: uri.href,
text: "App configuration here"
}]
})
);
// Dynamic resource with parameters
server.resource(
"user-profile",
new ResourceTemplate("users://{userId}/profile", { list: undefined }),
async (uri, { userId }) => ({
contents: [{
uri: uri.href,
text: `Profile data for user ${userId}`
}]
})
);
Tools
Tools let LLMs take actions through your server. Unlike resources, tools are expected to perform computation and have side effects:
// Simple tool with parameters
server.tool(
"calculate-bmi",
{
weightKg: z.number(),
heightM: z.number()
},
async ({ weightKg, heightM }) => ({
content: [{
type: "text",
text: String(weightKg / (heightM * heightM))
}]
})
);
// Async tool with external API call
server.tool(
"fetch-weather",
{ city: z.string() },
async ({ city }) => {
const response = await fetch(`https://api.weather.com/${city}`);
const data = await response.text();
return {
content: [{ type: "text", text: data }]
};
}
);
Prompts
Prompts are reusable templates that help LLMs interact with your server effectively:
server.prompt(
"review-code",
{ code: z.string() },
({ code }) => ({
messages: [{
role: "user",
content: {
type: "text",
text: `Please review this code:\n\n${code}`
}
}]
})
);
Contributing
Contributions are always welcome!
