What is the purpose of mCP Core?
It is the foundation for building intelligent, language‑driven backend services that interpret natural language commands and execute relevant tasks.
@brunosantoslab
基本情報
Foundational backend for MCP infrastructure.
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
mCP Core is the central monorepo for backend services and core logic powering a modular Machine Command Protocol (MCP) ecosystem. It serves as the foundation for building intelligent, language-driven backend services that interpret natural language commands and execute tasks like interacting with Docker, Git, or other developer tools.
—
It is the foundation for building intelligent, language‑driven backend services that interpret natural language commands and execute relevant tasks.
The monorepo houses servers that interact with tools like Docker, Git, and Visual Studio Code.
A monorepo provides unified structure, easier maintenance of shared logic, reusability, consistent code style/testing/CI‑CD, and modular growth without fragmenting the ecosystem.
The goals include using IA as an infrastructure interface, providing a scalable backend for natural‑language‑driven automation, enabling seamless integration with dev tools, and encouraging modular development with clean separation of responsibilities.
PickFu MCP is a Model Context Protocol (MCP) server that connects AI assistants, developers, marketers, product managers, and AI agents to PickFu's consumer research platform. It enables users to create surveys, conduct

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov
A search tool helps dev to solve the naming things problem.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
コメント