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registration.ts•4.04 kB
/** * @fileoverview Registration for the pubmed_research_agent tool. * @module pubmedResearchAgent/registration */ import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; import { CallToolResult } from "@modelcontextprotocol/sdk/types.js"; import { BaseErrorCode, McpError } from "../../../types-global/errors.js"; import { ErrorHandler, logger, RequestContext, requestContextService, } from "../../../utils/index.js"; import { pubmedResearchAgentLogic } from "./logic.js"; import { PubMedResearchAgentInput, PubMedResearchAgentInputSchema, } from "./logic/index.js"; /** * Registers the pubmed_research_agent tool with the MCP server. * @param server - The McpServer instance. */ export async function registerPubMedResearchAgentTool( server: McpServer, ): Promise<void> { const operation = "registerPubMedResearchAgentTool"; const toolName = "pubmed_research_agent"; const toolDescription = "Generates a standardized JSON research plan outline from component details you provide. It accepts granular inputs for all research phases (conception, data collection, analysis, dissemination, cross-cutting concerns). If `include_detailed_prompts_for_agent` is true, the output plan will embed instructive prompts and detailed guidance notes to aid the research agent. The tool's primary function is to organize and structure your rough ideas into a formal, machine-readable plan. This plan is intended for further processing; as the research agent, you should then utilize your full suite of tools (e.g., file manipulation, `get_pubmed_article_connections` for literature/data search via PMID) to execute the outlined research, tailored to the user's request."; const context = requestContextService.createRequestContext({ operation }); await ErrorHandler.tryCatch( async () => { server.tool( toolName, toolDescription, PubMedResearchAgentInputSchema.shape, async ( input: PubMedResearchAgentInput, mcpProvidedContext: unknown, ): Promise<CallToolResult> => { const richContext: RequestContext = requestContextService.createRequestContext({ parentRequestId: context.requestId, operation: "pubmedResearchAgentToolHandler", mcpToolContext: mcpProvidedContext, input, }); try { const result = await pubmedResearchAgentLogic(input, richContext); return { content: [ { type: "text", text: JSON.stringify(result, null, 2) }, ], isError: false, }; } catch (error) { const handledError = ErrorHandler.handleError(error, { operation: "pubmedResearchAgentToolHandler", context: richContext, input, rethrow: false, }); const mcpError = handledError instanceof McpError ? handledError : new McpError( BaseErrorCode.INTERNAL_ERROR, "An unexpected error occurred while generating the research plan.", { originalErrorName: handledError.name, originalErrorMessage: handledError.message, }, ); return { content: [ { type: "text", text: JSON.stringify({ error: { code: mcpError.code, message: mcpError.message, details: mcpError.details, }, }), }, ], isError: true, }; } }, ); logger.notice(`Tool '${toolName}' registered.`, context); }, { operation, context, errorCode: BaseErrorCode.INITIALIZATION_FAILED, critical: true, }, ); }

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