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60 projects
单一工作区，集 AI chat、resume builder、job matcher 和 website creation 工具于一体。
@multiai23 · X
🚀 MultiAI is LIVE! Start your FREE 7-day trial today! One platform. Multiple AI models. 📷 Access powerful AI tools from a single workspace. 📷 Code faster. 📷 Write better. #Claude #Gemini #live
通过统一的API访问多个AI代理，按使用量计费。
@agentsky_dev · X
Built for agents, not just models. AgentSky is live: one API to run Claude Code, Codex, DeepSeek, Kimi, OpenCode, and more in the cloud. Connect your real tools, then compare time, cost, and tokens side by side in Agent Playground. Try it:
为AI代理提供持久记忆和知识，支持文件、URL和MCP工具原生集成。
kitforai · GitHub
kitforai Kit for AI developer hub — official SDK, Claude Code plugin, MCP setup, and llms.txt.
Dash是连接3000多个工具的AI队友,自动化团队工作流程。
@dashpupai · X
Im Dash the best AI teammate for Slack
AI平台，提问、生成图像、语音交互，辅助更好的决策。
@Akinzoooo · X
为AI代理发行一次性虚拟Visa卡，带有可配置的消费预算。
keyserfaty · Product Hunt
Agentcard for companies Give your agent a debit card
用于并行运行 AI 编码 agent 的网页终端多路复用器
04mg · Product Hunt
Caw Open source web terminal multiplexer for AI agents
便携式记忆库，可在 Claude、ChatGPT、Cursor 等 AI 助手间持久保存。
u/OrganicArgument2092 · Reddit
I shipped Lodekeep: portable memory for AI agents that follows you across Claude, Cursor, and ChatGPT Every new AI chat starts from zero. Claude, Cursor, ChatGPT all forget my stack, my decisions, the gotchas I already solved, so I kept re-pasting the same context every single session. I got sick of it and built Lodekeep. You capture a decision, preference, or lesson once, and it's recallable in every future session across every MCP client (Claude web + desktop, Claude Code, Cursor, Gemini
为AI代理提供经济实惠的内存存储层。
@AudaxicTech · X
Memory for AI agents, most affordable in the industry
在平台上管理和同步你的AI Agent技能配置，避免供应商锁定。
@matebenyovszky · X
I use multiple providers Claude Code, Cursor, Codex, Hermes, Antigravity etc. and multiple machines. Over time, each one ended up with its own slightly different skills and tools 😰 So I started where a playbook is a portable bundle containing my MCP/OpenAPI servers, skills, prompts, personas and memory, which I can take with me into whichever environment I’m using. I’m still trying to figure out whether this is useful beyond my own workflow. Ideas? 🤔 🍎 Source / open source on Github: matebenyovszky/agentplaybooks I also built an npm CLI that audits a project and syncs the same skills and MCP definitions across harnesses.
发现并分享适用于Claude和Cursor的可复用AI智能体技能。
Skills.lc — AI 技能、Prompt、工作流和 Agent 分享平台，帮助发现和沉淀 AI 使用经验
