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Found 1,558 Skills
Comprehensive MCP tool reference for Proxmox Virtual Environment management - 92 tools across 14 domains including QEMU VMs, LXC containers, cluster operations, storage, networking, Ceph, certificates, ACME, and notifications
Use Neo4j memory MCP for creating/updating linked memories (entities, relations), de-duplication (DRY), and retrieval queries for project continuity. Use when saving global learnings or querying graph relationships.
Convert Figma designs into production-ready code using MCP server tools. Use this skill when users provide Figma URLs, request design-to-code conversion, ask to implement Figma mockups, or need to extract design tokens and system values from Figma files. Works with frames, components, and entire design files to generate HTML, CSS, React, or other frontend code.
Manages documents in Paperless-ngx via MCP tools. Searches, uploads, tags, organizes, and bulk-edits documents, correspondents, and document types. Use when working with Paperless-ngx, document management, OCR, or any mcp_paperless_* tool task.
Use when planning, scaffolding, validating, or packaging Claude skills inside Advanced Memory MCP.
Generate, validate and publish workflow, sequence and architecture diagrams, using FlowZap Code DSL. Use when the user asks to create a workflow, flowchart, sequence diagram, process map or architecture diagram. Produces .fz code and shareable playground URLs via the FlowZap MCP server or public API.
Use and troubleshoot the Memory MCP server for episodic memory retrieval and pattern analysis. Use when working with MCP server tools, validating the MCP implementation, or debugging MCP server issues.
MCP Status
Teaches AI assistants how to develop FlutterFlow apps using MCP tools. Use this skill when working with FlutterFlow projects, editing FF YAML, creating or inspecting pages and components, reading project configuration, or navigating FlutterFlow widget trees. It covers all 25 MCP tools for discovery, reading, editing, and settings. Triggers on: FlutterFlow, FF YAML, FF page, FF component, FF widget, FF theme, FF project.
Intelligent Retrieval Assistant for Cangjie Language Documentation. Supports 4 search modes (Direct Search, PageIndex Intelligent Retrieval, Hybrid Mode, Exploratory Learning). It is used when users need to: (1) Query Cangjie syntax (variable declaration, function definition, generics, etc.), (2) Look up standard library APIs (String, Array, HashMap, etc.), (3) Learn about Cangjie features or get started with the language, (4) Conduct any documentation queries related to Cangjie/cangjie/cj. It uses four MCP tools: cangjie_docs_overview, cangjie_list_docs, cangjie_search, and cangjie_get_doc for intelligent retrieval.
Query Light Protocol and related repositories via DeepWiki MCP. Use when answering questions about compressed accounts, Light SDK, Solana development, Claude Code features, or agent skills. Triggers on technical questions requiring repository context.
创建高质量 MCP（模型上下文协议）服务器的指南，使 LLM 能够通过精心设计的工具与外部服务交互。在构建 MCP 服务器以集成外部 API 或服务时使用，无论是 Python (FastMCP) 还是 Node/TypeScript (MCP SDK)。