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Found 476 Skills
CCDB Carbon Emission Factor Search Tool. Based on Carbonstop's CCDB database, query carbon emission factor data via ccdb-mcp-server. Supports keyword-based carbon emission factor search, retrieval of structured JSON data, and multi-keyword comparison. **Use this Skill when**: (1) Users query carbon emission factors (e.g., "power emission factor", "cement carbon emission", "natural gas emission coefficient", etc.) (2) Users need to calculate carbon emissions (require querying factors first then multiplying by activity volume) (3) Users need to compare carbon emission factors of different energy sources/materials (4) Users mention "CCDB", "carbon emission factor", "emission coefficient", "carbon footprint", "LCA", "emission factor" (5) Need to query carbon emission factor data for specific countries/regions and specific years
Use when researching, compiling, or assessing best practices for any AWS service, building HA/DR/security checklists from official AWS documentation, or checking whether live AWS resources follow official recommendations. Requires aws-knowledge-mcp-server. Triggers on "best practices", "compile checklist", "summarize HA/DR best practices", "what are the best practices for", "find all best practices", "check my cluster", "audit my redis", "assess my redis", "assessment", "是否符合最佳实践", "检查现有资源", "查找最佳实践", "编译检查清单", "总结最佳实践", "帮我查找", "汇总成表", "帮我检查", "审计一下", "评估一下".
Super LinkedIn for the terminal. Search, enrich, and map warm-intro paths across LinkedIn (stickerdaniel/linkedin-mcp-server subprocess), Happenstance (cookie-first free quota with bearer-API fallback), and Deepline (paid enrichment). Two Happenstance auth surfaces coexist: Chrome cookie session (free monthly allocation) and HAPPENSTANCE_API_KEY bearer (paid credits, deeper schema). Use when the user asks who they know at a company, how to get a warm intro, who to prospect, or wants cross-source dossiers, network diffs, or waterfall enrichment.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Query the OpenAI developer documentation via the OpenAI Docs MCP server using CLI (curl/jq). Use whenever a task involves the OpenAI API (Responses, Chat Completions, Realtime, etc.), OpenAI SDKs, ChatGPT Apps SDK, Codex, MCP integrations, endpoint schemas, parameters, limits, or migrations and you need up-to-date official guidance.
AI 에이전트 실전 워크플로우와 생산성 기법. 명령어, 단축키, Git 통합, MCP 활용, 세션 관리 등 일상 개발 작업의 최적화 패턴 제공.
Configure an MCP server for GitHub Copilot with your Dataverse environment.
Give an AI agent its own real browser over MCP tool calls - launch, navigate, click, fill, screenshot, extract text, run JS - with a kernel-level real-device fingerprint and a persistent profile, so the session stays logged in between runs and pages see one coherent device instead of a headless build. No Playwright or SDK code to write. Use when an agent should operate a site itself, when a computer-use / browser-use setup needs a captured real fingerprint rather than a synthetic one, when agent sessions keep losing their login, or when comparing hosted agent-browser services. Also for 'MCP browser', 'browser MCP server', 'let my agent browse the web', 'agent browser control', 'browser-use MCP', 'computer use browser', 'Browserbase alternative', 'Steel browser alternative', 'headless browser detected'. Node (npx) or Python; Windows x64, macOS Intel + Apple Silicon, Linux x64 / arm64. SDK and REST reference is anti-detect-browser; account isolation is multi-account-isolation.
Search live flight fares for a route and date across Agoda, Trip.com, and Traveloka — one-way or round-trip, any cabin, with airline, times, stops, duration, and a direct booking link. Use when the user wants flight prices, plane or air tickets, cheap flights or airfare between two cities, comparing airlines for travel dates, or planning the flying leg of a trip.
Configure Azure API Management (APIM) as AI Gateway to secure, observe, control AI models, MCP servers, agents. Helps with rate limiting, semantic caching, content safety, load balancing. USE FOR: AI Gateway, APIM, setup gateway, configure gateway, add gateway, model gateway, MCP server, rate limit, token limit, semantic cache, content safety, load balance, OpenAPI import, convert API to MCP. DO NOT USE FOR: deploy models (use microsoft-foundry), Azure Functions (use azure-functions), databases (use azure-postgres).
Bare minimum setup for getting started with Firebase for the agent. This covers Node.js installation, Firebase CLI availability, login, and MCP server installation. Use this to ensure the local environment is fully prepared before using Firebase.
Agent onboarding for Orderly Network - omnichain perpetual futures infrastructure, MCP server, skills, and developer quickstart