☁️ 云服务 — Top 10 AI Agent 工具
AWS、GCP、Azure、阿里云——用自然语言管理云资源,开服务器、配权限、查账单都能说话搞定。适合需要频繁操作云控制台的开发者和运维,把点点点变成一句话。
共收录 187 个工具 · 显示评分最高 10 个
awslabs/mcp
精选PythonOpen source MCP Servers for AWS
webiny/webiny-js
精选TypeScriptOpen-source, self-hosted CMS platform on AWS serverless (Lambda, DynamoDB, S3). TypeScript framework with multi-tenancy, lifecycle hooks, GraphQL API, and AI-assisted development via MCP server. Built
refly-ai/refly
精选TypeScriptThe first open-source agent skills builder. Define skills by vibe workflow, run on Claude Code, Cursor, Codex & more. Build Clawdbot 🦞· APIs for Lovable · Bots for Slack & Lark/Feishu · Skills are inf
microsoft/SkillOpt
精选PythonSkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.
pip install -e .crmne/ruby_llm
精选RubyOne beautiful Ruby API for OpenAI, Anthropic, Gemini, Bedrock, Azure, OpenRouter, DeepSeek, Ollama, VertexAI, Perplexity, Mistral, xAI, GPUStack & OpenAI compatible APIs. Agents, Chat, Vision, Audio,
microsoft/mcp
精选C#Catalog of official Microsoft MCP (Model Context Protocol) server implementations for AI-powered data access and tool integration
punkpeye/fastmcp
精选TypeScriptA TypeScript framework for building MCP servers.
npm install fastmcprilldata/rill
精选GoThe fastest business intelligence tool for humans and agents.
griptape-ai/griptape
精选PythonModular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.
microsoft/skills
精选TypeScriptSkills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents
💡 如何选择合适的 云服务 工具?
评分是怎么算的?+
Trove 的评分包含 4 个维度:文档质量(Doc)、代码质量(Code)、社区活跃度(Community)和近期更新(Activity),总分 25 分,并划分为精选(≥20)、已验证(≥12.5)、社区(<12.5)三档。
如何选择适合自己的工具?+
先看 tier(精选/已验证优先),再看 stars 和近期更新时间,最后看 install_hint 确认安装方式是否符合你的环境(npm/pip/go 等)。
这些工具支持哪些 AI 平台?+
大多数工具以 MCP 协议为标准,兼容 Claude、OpenClaw、Codex、Cursor 等主流 AI 平台。部分工具还提供 OpenAI Function / LangChain Tool 格式。
如何把自己的工具上榜?+
在 GitHub 发布你的工具,带上相关 topic(如 mcp-server、ai-agent-skills),Trove 的爬虫会自动收录并评分。也可以到 opentrove.ai/publish 主动提交。