mcp-ts-template
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A production-grade TypeScript template for building robust Model Context Protocol (MCP) servers, featuring built-in observability with OpenTelemetry, advanced error handling, comprehensive utilities, and a modular architecture.
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JavaScript
/**
* @fileoverview Handles registration of the `fetch_image_test` tool.
* This module acts as the "handler" layer, connecting the pure business logic to the
* MCP server and ensuring all outcomes (success or failure) are handled gracefully.
* @module src/mcp-server/tools/imageTest/registration
* @see {@link src/mcp-server/tools/imageTest/logic.ts} for the core business logic and schemas.
*/
import { BaseErrorCode } from "../../../types-global/errors.js";
import { ErrorHandler, logger, measureToolExecution, requestContextService, } from "../../../utils/index.js";
import { FetchImageTestInputSchema, fetchImageTestLogic, FetchImageTestResponseSchema, } from "./logic.js";
/**
* The unique name for the tool, used for registration and identification.
* Include the server's namespace if applicable, e.g., "pubmed_fetch_article".
*/
const TOOL_NAME = "fetch_image_test";
/**
* Detailed description for the MCP Client (LLM), explaining the tool's purpose, expectations,
* and behavior. This follows the best practice of providing rich context to the MCP Client (LLM) model. Use concise, authoritative language.
*/
const TOOL_DESCRIPTION = "Fetches a random cat image from an external API (cataas.com) and returns it as a blob. Useful for testing image handling capabilities.";
/**
* Registers the fetch_image_test tool with the MCP server.
* @param server - The McpServer instance.
*/
export const registerFetchImageTestTool = async (server) => {
const registrationContext = requestContextService.createRequestContext({
operation: "RegisterTool",
toolName: TOOL_NAME,
});
logger.info(`Registering tool: '${TOOL_NAME}'`, registrationContext);
await ErrorHandler.tryCatch(async () => {
server.registerTool(TOOL_NAME, {
title: "Fetch Cat Image",
description: TOOL_DESCRIPTION,
inputSchema: FetchImageTestInputSchema.shape,
outputSchema: FetchImageTestResponseSchema.shape,
annotations: {
readOnlyHint: true,
openWorldHint: true,
},
}, async (input, callContext) => {
const sessionId = typeof callContext?.sessionId === "string"
? callContext.sessionId
: undefined;
const handlerContext = requestContextService.createRequestContext({
parentContext: callContext,
operation: "HandleToolRequest",
toolName: TOOL_NAME,
sessionId,
input,
});
try {
const result = await measureToolExecution(() => fetchImageTestLogic(input, handlerContext), { ...handlerContext, toolName: TOOL_NAME }, input);
return {
structuredContent: result,
content: [
{
type: "image",
data: result.data,
mimeType: result.mimeType,
},
],
};
}
catch (error) {
const mcpError = ErrorHandler.handleError(error, {
operation: `tool:${TOOL_NAME}`,
context: handlerContext,
input,
});
return {
isError: true,
content: [{ type: "text", text: `Error: ${mcpError.message}` }],
structuredContent: {
code: mcpError.code,
message: mcpError.message,
details: mcpError.details,
},
};
}
});
logger.notice(`Tool '${TOOL_NAME}' registered.`, registrationContext);
}, {
operation: `RegisteringTool_${TOOL_NAME}`,
context: registrationContext,
errorCode: BaseErrorCode.INITIALIZATION_FAILED,
critical: true,
});
};
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