Mirror of https://github.com/mzxrai/mcp-webresearch

A lightweight, multi-format content fetcher enabling on-demand HTML, JSON, TXT, and Markdown outputs with format conversion.

Unifies LinkedIn feeds and job data via an unofficial API for programmable, seamless access.

Integrates Google Tasks with a modular backend, offering search, list, create, update, delete, and local OAuth credential flow.

Downloads YouTube subtitles with yt-dlp and connects to Claude via Model Context Protocol for quick AI-assisted video insights.

Python-based daemon to orchestrate Model Context Protocol engines with Docker packaging and multi-instance control.

CLI-driven broker enabling discovery, installation, and secure orchestration of MCP components via Docker-based isolation.

Automated security analysis toolkit orchestrating multi-tool checks with Docker isolation and centralized reporting for MCP implementations.

Generates customizable context environments with automated file creation, tool management, and robust debugging for rapid development workflows.

In this project, we will explore how the problem of the Multiple Couriers Planning (MCP) is modeled and discuss various approaches to address it: Constraint Programming (CP), Satisfiability Modulo Theories (SMT) and Mixed-Integer Linear Programming (MIP).