Awesome/awesome-mcp-servers
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Muhammad Hamza
2025-09-01 21:17:54 +05:00
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@@ -486,7 +486,7 @@ Tools and integrations that enhance the development workflow and environment man
- [freema/mcp-design-system-extractor](https://github.com/freema/mcp-design-system-extractor) 📇 🏠 - Extracts component information from Storybook design systems. Provides HTML, styles, props, dependencies, theme tokens and component metadata for AI-powered design system analysis.
- [gitkraken/gk-cli](https://github.com/gitkraken/gk-cli) 🎖️ 🏎️ 🏠 ☁️ 🍎 🪟 🐧 - A CLI for interacting with GitKraken APIs. Includes an MCP server via `gk mcp` that not only wraps GitKraken APIs, but also Jira, GitHub, GitLab, and more. Works with local tools and remote services.
- [GLips/Figma-Context-MCP](https://github.com/GLips/Figma-Context-MCP) 📇 🏠 - Provide coding agents direct access to Figma data to help them one-shot design implementation.
- [mhmzdev/Figma-Flutter-MCP](https://github.com/mhmzdev/Figma-Flutter-MCP) 🎨 📲 - Provide coding agents direct access to Figma data to help them write Flutter code for building apps including assets exports, widgets maintenance and full screens implementations.
- [mhmzdev/Figma-Flutter-MCP](https://github.com/mhmzdev/Figma-Flutter-MCP) 📇 🏠 - Provide coding agents direct access to Figma data to help them write Flutter code for building apps including assets exports, widgets maintenance and full screens implementations.
- [gofireflyio/firefly-mcp](https://github.com/gofireflyio/firefly-mcp) 🎖️ 📇 ☁️ - Integrates, discovers, manages, and codifies cloud resources with [Firefly](https://firefly.ai).
- [gorosun/unified-diff-mcp](https://github.com/gorosun/unified-diff-mcp) 📇 🏠 - Generate and visualize unified diff comparisons with beautiful HTML/PNG output, supporting side-by-side and line-by-line views for filesystem dry-run integration
- [Govcraft/rust-docs-mcp-server](https://github.com/Govcraft/rust-docs-mcp-server) 🦀 🏠 - Provides up-to-date documentation context for a specific Rust crate to LLMs via an MCP tool, using semantic search (embeddings) and LLM summarization.