server-config.ts•3.56 kB
/**
* @file MCP Server configuration and capabilities - Example Implementation
* @module constants/server/server-config
*
* @remarks
* This module defines the server metadata and capabilities for this example MCP server
* implementation. It demonstrates how to properly configure a type-safe MCP server
* that implements the full MCP specification including tools, prompts, resources,
* sampling, and OAuth 2.1 authentication.
*
* This serves as a reference implementation for developers building their own MCP servers.
*
* @see {@link https://modelcontextprotocol.io/specification/2025-06-18/server | MCP Server Specification}
*/
import type { Implementation, ServerCapabilities } from "@modelcontextprotocol/sdk/types.js";
/**
* Server implementation metadata
*
* @remarks
* Provides identifying information about this example MCP server implementation.
* This demonstrates proper type-safe configuration with full specification support.
*
* Key features demonstrated:
* - Complete MCP specification implementation
* - Type-safe TypeScript architecture
* - Production-ready patterns and best practices
* - OAuth 2.1 authentication flow
* - Real-world API integration (Reddit)
*/
export const serverConfig: Implementation = {
name: "brainloop-mcp-server",
version: "2.0.0",
metadata: {
name: "BRAINLOOP MCP Server",
description:
"BRAINLOOP MCP server for personalized learning data access. " +
"Provides batch operations for courses, units, lessons, and progress tracking. " +
"Built with OAuth 2.1 authentication and production-ready architecture.",
icon: "brain",
color: "blue",
serverStartTime: Date.now(),
environment: process.env.NODE_ENV || "production",
customData: {
serverType: "brainloop-production",
implementationFeatures: [
"batch-operations",
"course-management",
"lesson-creation",
"progress-tracking",
"oauth-2.1",
"type-safe",
"production-ready"
],
integration: "brainloop-api",
supportedOperations: [
"create-course-batch",
"create-unit-batch",
"create-lesson-batch",
"get-my-courses",
"search-lessons",
"get-progress"
],
},
},
};
/**
* Server capabilities declaration
*
* @remarks
* This declares all MCP capabilities that this example server supports.
* Each capability corresponds to a feature in the MCP specification:
*
* - tools: Interactive functions the AI can call
* - sampling: AI content generation with human approval
* - prompts: Predefined prompt templates
* - resources: Dynamic content the AI can read
* - logging: Server-side logging capability
*
* This example implements ALL capabilities to serve as a complete reference.
*/
export const serverCapabilities: { capabilities: ServerCapabilities } = {
capabilities: {
tools: {}, // Full tool support with type-safe handlers
sampling: {}, // Complete sampling implementation with callbacks
prompts: {}, // Dynamic prompt generation
resources: {}, // Resource listing and reading
logging: {}, // Client-requested logging support
},
};
/**
* Additional server configuration constants
*/
export const SERVER_CONFIG = {
SESSION_TIMEOUT: 30 * 60 * 1000,
MAX_SESSIONS: 100,
RATE_LIMIT: {
windowMs: 60000, // 1 minute
maxRequests: 100,
},
MAX_REQUEST_SIZE: 10 * 1024 * 1024, // 10MB
PROTOCOL_VERSION: "2025-06-18",
SDK_VERSION: "@modelcontextprotocol/sdk@1.13.0",
} as const;