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AI-редактор кода, часто используемый с developer MCP.
MCP Servers
A middleware server that enables multiple isolated instances of the same MCP servers to coexist independently with unique namespaces and configurations.
Discover, install and manage MCP servers on macOS
- The docker image is 2GB without pre-downloaded models. Its 3.76GB with pre-downloaded models!! Too big, someone please help me to reduce the size.
Python MCP Server for Kestra — you can use it as a tool in Kestra's AI Agents
Frame0 is a Balsamiq-alternative wireframe tool for modern apps. allows you for creating and modifying wireframes in Frame0 by prompting.
iPhone MCP server that lets AI use iPhones
Package bug screenshots into AI-ready fix instructions with MCP Server
MCP server for Nordic grocery deal hunting via the Tjek API (Denmark, Norway, Sweden, Finland)
91% of Deep Research quality · 5% of the cost · Works in every MCP client
- the original community MCP server for Unusual Whales by Erik Maday.
这是一个支持远程连接的模型上下文协议 (MCP) 服务器，内置了飞书 OAuth 认证。
Wot UI 的 AI 能力工具集：Skills、MCP 协议与 CLI 工具等
Agent Skills
The main repository for libraries used to build applications on the Atsign Platform. Three categories: SDKs, libraries, and Flutter widgets.
is an API-first Ruby web framework that combines the developer experience of Rails with fiber-based concurrency.
本项目是基于吴恩达老师在 DeepLearning.AI 平台推出的 agent-skills-with-anthropic 系列课程的中文学习资料整理项目。我们致力于为中文学习者提供高质量的课程内容翻译、系统的知识点梳理以及详细的示例代码解读，帮助大家更轻松地掌握 Agent Skills。
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upfetch is an advanced fetch client builder with standard schema validation, automatic response parsing, smart defaults and more.
A collection of Pi Coding Agent customized instances. Why? To showcase what it looks like to hedge against the leader in the agentic coding market, Claude Code.
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SkillsBench evaluates how well skills work and how effective agents are at using them.
Website • Getting Started • Documentation • Community
KAI Scheduler is a robust, efficient, and scalable Kubernetes scheduler that optimizes GPU resource allocation for AI and machine learning workloads.
An interactive five-chapter night walk through a Kyoto mountain temple, rendered live in Three.js.
For more advanced capabilities and end-to-end machine learning, visit www.k-dense.ai.