MCP Meeting Agent

""" LangChain tools for meeting preparation functionality. """ from langchain.tools import tool from ..services.tech_trivia_service import TechTriviaService from ..services.fun_facts_service import FunFactsService from ..services.github_trending_service import GitHubTrendingService from ..formatters.repository_formatter import RepositoryFormatter from ..prompts.fallback_prompts import ( TECH_TRIVIA_FALLBACK_PROMPT, FUN_FACT_FALLBACK_PROMPT, TRENDING_REPOS_FALLBACK_PROMPT ) from . import tool_error_handler @tool @tool_error_handler( TECH_TRIVIA_FALLBACK_PROMPT, "Question: What programming language was created by Guido van Rossum?\nAnswer: Python" ) async def get_tech_trivia(ctx=None) -> str: """Get a technology trivia question and answer for meeting icebreakers with LLM fallback.""" service = TechTriviaService() trivia = await service.get_tech_trivia() return f"Question: {trivia.question}\nAnswer: {trivia.correct_answer}" @tool @tool_error_handler( FUN_FACT_FALLBACK_PROMPT, "Did you know? The average person spends 6 months of their life waiting for red lights." ) async def get_fun_fact(ctx=None) -> str: """Get an interesting fun fact for meeting engagement with LLM fallback.""" service = FunFactsService() fact = await service.get_fun_fact() return fact.text @tool @tool_error_handler( TRENDING_REPOS_FALLBACK_PROMPT, """• langchain-ai/langchain - Building applications with LLMs through composability • openai/openai-python - The official Python library for the OpenAI API • microsoft/vscode - Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications""" ) async def get_trending_repos(ctx=None) -> str: """Get current trending GitHub repositories for tech discussions with LLM fallback.""" service = GitHubTrendingService() repos = await service.get_trending_repos() return RepositoryFormatter.format_trending_repos_for_llm(repos)