技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: manage-databases

英文目录

Build, run, and manage agent platforms.

42K
Stars
84/100
信任
分类: agent-frameworks审计

Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.

33K
Stars
88/100
信任
分类: data-analysis审计

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

30K
Stars
87/100
信任
分类: rag-knowledge审计

Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.

22K
Stars
80/100
信任
分类: data-analysis审计

Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.

40K
Stars
85/100
信任
分类: coding-agents审计

A comprehensive collection of ready-to-use scientific and research skills for AI agents.

31K
Stars
78/100
信任
分类: utility审计
K9s77

🐶 Kubernetes CLI To Manage Your Clusters In Style!

34K
Stars
77/100
信任
分类: devops审计

SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled.

32K
Stars
87/100
信任
分类: rag-knowledge审计

A docker-powered PaaS that helps you build and manage the lifecycle of applications

32K
Stars
83/100
信任
分类: devops审计

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

11K
Stars
87/100
信任
分类: ml-automation审计

Empowering Data Intelligence with Distributed SQL for Sharding, Scalability, and Security Across All Databases.

21K
Stars
86/100
信任
分类: data-analysis审计

SQL databases in Python, designed for simplicity, compatibility, and robustness.

18K
Stars
85/100
信任
分类: data-analysis审计