AI 智能体5 days ago
ReadReceipt | Know when to follow up after you send a PDF
追踪PDF浏览互动，自动为提案和演讲稿生成后续跟进消息的AI代理。
@Naftali_JR · X
Document engagement tracking
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追踪PDF浏览互动，自动为提案和演讲稿生成后续跟进消息的AI代理。
@Naftali_JR · X
Document engagement tracking
用你的声音自动管理X账户、发布帖子、回复和直接消息的AI代理。
@mukparekh · X
与AI聊天自动调研、撰写和生成排版好的小册子。
BookletAI — 面向普通用户的小册子 AI 工具，可自动调研、写作并生成排版好的 booklet 页面。
构建共享知识图谱，为AI代理组织团队背景信息。
ximihoque · HN
Collaborative context-sharing memory platform for agents and teams
检测AI代理失控循环,自动生成验证补丁和修复PR。
@void_rags · X
Introducing Orqis AI, an AI Watchdog that also fixes Agents. Have a look:
Gate 为 AI 代理提供安全防护,防止提示词注入、扫描秘密并节省代币。
benjamin_jorgensen1 · Product Hunt
Constellation Gate AI Prompt injection and token savings - #1 in benchmarks
托管 JSON 数据库，用于存储 agent 内存，具有 REST 和 MCP 连接能力
@StuSim · X
hey Adam, I run , lightweight agent memory
统一SMS和电子邮件的AI收件箱，支持自动回复和每日智能摘要。
u/Forsaken_Coconut3717 · Reddit
Anyone down to test each other's tools? (socks stay on) Hey all! I've been a lurker for a number of years and I think it's finally time for me. I built a tool that I think might actually be worth something! At its core it basically unifies every customer’s texts and emails into one shared conversation and is built for setting up AI agents to run your communications right from within the platform. It has a lot of moving parts but I think it can genuinely be the next big platform for man
从社交、链上和链外数据中合成交易信号的AI代理。
@orbitant · X
Elfa just launched Iris. If you're looking for api to connect your agents for synthesises signals across social, on-chain, and off-chain market data etc 1000 credits free monthly API for your vibe coding:
销售团队的AI代理，自动处理邮件、会议和CRM任务。
syed_ahsan2 · Product Hunt
Agent07 Sales Agents - makes sales 2x faster
在云平台构建和部署AI代理，支持持久线程、Webhook和计划任务。
@computer_agents · X
A vendor-neutral home for AI agent skills, personas, MCP servers, project instructions, and memory. Keep your setup portable and in sync across platforms without vendor lock-in.
@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.