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개발자용 MCP 서버와 함께 자주 쓰이는 AI 코드 에디터.
MCP Servers

An MCP Server to enable global access to Rememberizer

Maintenance of a set of tools to enhance LLM through MCP protocols.

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This project implements a Model Context Protocol (MCP) server for GitHub API access. It provides a set of tools that allow LLM agents to interact with GitHub repositories, issues, pull requests, and...

A Model Context Protocol (MCP) server implementation that provides Facebook Page interaction and management capabilities.

https://www.youtube.com/watch?v=KQpxiXvF4cc

By transforming source code into a queryable Semantic Graph and a structured AST, this tool bridges the gap between "reading text" and "understanding structure.

Model Context Protocol (MCP) server for Multi-Cloud Infrastructure Diagrams

Apple Store Connect MCP Server for Claude AI - iOS-compatible OAuth with comprehensive App Store Connect API integration

This is a Model Context Protocol (MCP) server that allows executing JMeter tests through MCP-compatible clients and analyzing test results.

Python MCP server for BitDive trace analysis, request reproduction, and regression management.

A Model Context Protocol (MCP) server that enables AI assistants to execute KQL queries and explore Azure Data Explorer (ADX/Kusto) databases through standardized interfaces.
Agent Skills

SigNoz Website

Open-source Claude Code plugin porting the internal /skillify skill: turn a finished session's repeatable workflow into a reusable SKILL.md you can rerun with a slash command.

Claude Code skill + Remotion scaffold for building polished product launch videos.

Permissionless infrastructure for agents. No human intervention required.

Develop Swift/iOS projects using VSCode

Sync and store bookmarks locally, manage Field Theory Library and command workflows, and make local context available to Claude Code, Codex, or any agent with shell access.

如果在使用过程中遇到问题,请通过 Issues 反馈功能正确性问题和功能请求,其他问题请通过 Discussions 反馈~

VS Code in the terminal

Generate app icon artwork and Google Play feature graphics from the terminal with OpenAI or Google Gemini.

Fill-in-your-own-data framework for YouTube / short-form video automation: CapCut JSON + ffmpeg tooling + an onboarding questionnaire. Ships with zero private data.

🚧 We are actively refining our core, resumption protocols, and runtime specifications, which will introduce major breaking changes prior to a stable release.
One Python API: store media, run models, index embeddings, serve endpoints, and version everything in a single system instead of gluing together blob storage, a vector DB, an orchestrator, and edge...