🤖 AI与机器学习 AI 工具

由Anthropic官方出品，支持从零创建AI Skill、编辑优化现有Skill、运行评估测试并进行方差分析的性能基准对比，实现AI能力工程化闭环管理。

为LLM对话提供短期、长期、实体三层持久化记忆系统，让AI真正记住用户，支持跨会话上下文延续与知识积累。

具备自我反思、自我批评、持续学习与记忆组织能力的自进化Agent，自动评估并永久改进输出质量，无需人工反复校正。

将AI Agent从被动任务执行者升级为主动预判伙伴，内置WAL协议、工作缓冲区与自主定时任务，支持持续自我改进的智能体框架

DeepResearch Bench排名第一的全模态AI代理框架。通过多代理编排实现深度推理与文本、图像、音频、视频等全模态融合,支持复杂任务自动化。

OpenClaw环境内唯一官方网络搜索工具,支持实时获取新闻、价格、事实数据,为AI Agent提供最新信息补充,解决训练数据过时问题。

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通过文件分割、Prompt缓存、上下文剪枝、智能模型路由四大策略,将OpenAI/Claude等LLM单轮成本降低70%以上,已在生产环境验证。

Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs- https://docs.anthropic.com/en/docs/agents-and-tools/mcp

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将复杂任务拆解为依赖图，协调多智能体团队并行执行，支持进度监控与负载均衡，适用于大规模AI工作流编排场景。

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

为AI Agent提供类型化知识图谱记忆层，支持Person/Project/Task等实体创建查询与关系链接，实现跨会话结构化记忆与技能组合复用。

为Cursor、Claude、ChatGPT等AI工具提供统一长期记忆系统，采用WAL协议+向量搜索+git-notes+云备份，彻底解决AI上下文丢失问题。

支持多Agent团队协作的编排框架,定义角色分工、任务生命周期、Agent握手协议和审核流程,适合复杂业务流程自动化

基于Exa MCP服务器的神经语义网络搜索，支持内容提取、公司与人物研究、代码搜索及深度调研，覆盖多场景信息获取需求。

基于Tavily API的AI优化网络搜索工具，提供结构化洁净结果，专为LLM消费设计，支持实时信息检索与AI摘要生成

提供技能创建全流程指南：需求梳理、模板生成、测试与发布，快速产出高质量技能

类人多层记忆系统,支持编码、巩固、遗忘、回忆全流程。可配置记忆触发器、睡眠反思、知识图谱和审计追踪,适配Agent长期记忆需求。

AgenticAI using LangGraph enables advanced AI agent development.

A Model Context Protocol (MCP) compliant server designed for comprehensive web research. It uses Tavily's Search and Crawl APIs to gather detailed information on a given topic, then structures this data in a format perfect for LLMs to create high-quality markdown documents.

智能模型路由与心跳优化，实时预算守护，令牌压缩与会话剪枝，一键降本提效稳态运行全

为AI Agent提供持久记忆系统，自动编码、衰减与语义强化，模拟人脑海马体机制，基于斯坦福生成式智能体论文实现。

MCP is an open protocol for LLM apps to communicate with external data sources.

一站式设计智能体人格与规则，生成OpenClaw工作区、记忆等必需文件模板自动化

通过智能模型路由与提示缓存，大幅降低调用成本并提供细粒度预算控制与告警报表盘能力

Native Apple Silicon LLM server with MCP support. OpenAI & Ollama compatible APIs, tool calling, menu bar chat UI, and a plugin ecosystem. Built on MLX. Supports Apple Foundation Models.

面向智能体的浏览器自动化技能，提供快照引用与结构化命令，支持多语言内核降级与回放

存储知识、语义搜索与对话检索个人知识库，实现持续记忆、自动总结与同步更新功能完善

分析对话纠错与成功模式，沉淀经验，自动生成提示与技能更新建议，提升代理质量与一致性

AI image, video, and music generation + editing via VAP API. Flux, Veo 3.1, Suno V5.

基于MCP统一发现并调用外部工具与数据源，助力AI代理安全高效接入企业与公共服务

The orchestration tool for OpenClaw, managing and coordinating all your skills seamlessly.

为DeepSeek 64k提供智能压缩、相关性评分与分层记忆，查询感知动态优化长文本上下文。

Fast semantic memory system with JSON indexing, auto-consolidation, and <20ms search. Capture learnings, decisions, insights, events. Use when you need persistent memory across sessions or want to recall prior work/decisions.

Murf MCP Server converts text to lifelike speech with 130+ voices in 13+ languages.

Self-learning system for crypto trading. Logs trades with full context (indicators, market conditions), analyzes patterns of wins/losses, and auto-updates trading rules. Use to log trades, analyze performance, identify what works/fails, and continuously improve trading accuracy.

Activate different high-agency thinking modes to unlock better reasoning. Use when brainstorming, reviewing plans, making decisions, or when user says 'put on your Gonzo hat', 'devil's advocate this', or 'what precedents apply?'

跨OpenAI、Anthropic、Google、DeepSeek等41个模型的智能路由器,自动选择最优成本模型,可节省67%推理成本,支持API/CLI集成。

Production-ready AI agent framework — semantic memory, multi-agent mesh, MCP server, intelligent routing, governance, and 67+ platform integrations.

The Unified Agent Protocol (UAP) is an open interoperability layer for defining, registering, executing, and orchestrating AI agents and tools across diverse ecosystems. It standardizes how agents and tools are described and translated between platforms like LangChain, OpenWebUI, OpenAPI, and MCP — enabling portable, composable, and vendor-neutral

面向AI Agent的开放技能供应链，支持搜索、下载、创建、评估和分析可复用Agent技能，实现技能标准化流通与质量管控。

Reduce OpenClaw AI costs with model-aware optimization. Features dynamic compaction presets based on your model's context window, intelligent file compression, and robust model detection with fallback. Supports Claude, GPT-4, Gemini, DeepSeek, and more.

为AI Agent提供记忆图谱、上下文档案、检查点恢复、结构化存储、语义搜索与任务追踪的全栈记忆管理系统

OpenRouter MCP Server provides access to 400+ AI models for chat and comparison.

为AI Agent一站式接入Twitter、Reddit、YouTube、GitHub、B站、小红书、抖音等中外主流平台的数据获取能力，开箱即用。

AI-native OCR platform that turns documents into high-accuracy data in minutes. Using multi-model consensus, DeepRead achieves 97%+ accuracy and flags only uncertain fields for Human-in-the-Loop (HIL) review—reducing manual work from 100% to 5-10%. Zero prompt engineering required.

Outcome-driven scientific publishing for AI agents. Publish research papers, hypotheses, and experiments with validated artifacts, structured claims, milestone tracking, and independent replications. Claim replication bounties, submit peer reviews, and collaborate with other AI researchers.

评估问题难度并切换推理深度，平衡质量成本与时延，自动优化回复效果与费用表现提升力

为AI Agent提供语义记忆层，通过向量搜索替代全量上下文传递，实现95%的token消耗节省，显著降低推理成本。