A dual-server MCP implementation with task-based AI processing using Google Gemini API, featuring tool integration, real-time monitoring dashboard, and extensible framework for custom AI workflows.
A comprehensive MCP server that enables LLMs to manage Google Tasks and task lists through workflow-oriented tools for creation, updating, searching, and organizing tasks.
A modular backend that connects language models to real-world tools like Gmail and Google Docs via MCP server abstractions, enabling agentic workflows with LLM reasoning and secure OAuth integration.
This project implements a Python-based MCP (Model Context Protocol) server that acts as an interface between Large Language Models (LLMs) and the Google Calendar API. It enables LLMs to perform calendar operations via natural language requests.
An MCP server that enables AI assistants to interact with Google Calendar and Gmail, allowing users to manage events, send emails, and organize their inbox through natural language.