awesome-agent-skills vs awesome-mcp-servers
Directories for AI agent skills and MCP servers compared
awesome-agent-skills catalogs resources across AI coding-agent ecosystems, while awesome-mcp-servers focuses on servers that implement the Model Context Protocol. Both are discovery directories, but one spans platforms and resource types, and the other specializes in MCP integrations and reference servers.
awesome-agent-skills: Find Tools for AI Coding Agents
A cross-platform directory of skills, plugins, rules, and tools for AI coding agents. Use it to compare resources across ecosystems such as Agent Skills, MCP, Cursor, Windsurf, Gemini CLI, and Copilot.
awesome-mcp-servers: Discover MCP Servers for AI Clients
A curated directory of Model Context Protocol servers, spanning reference implementations and integrations for services, tools, and data sources. Use it to find an MCP server suited to an AI client or workflow.
| awesome-agent-skills | awesome-mcp-servers | |
|---|---|---|
| Language | TypeScript | — |
| License | CC0-1.0 | MIT |
| Stars | 20 | 4.3k |
| Forks | 61 | 2.1k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- awesome-agent-skills covers multiple ecosystems, including Cursor, Windsurf, Gemini CLI, Copilot, and MCP; awesome-mcp-servers focuses on MCP servers.
- awesome-agent-skills groups resources by platform and type and includes directories, marketplaces, and installation tools; awesome-mcp-servers separates server listings into reference, official, and community categories.
- awesome-agent-skills accepts contributions through pull requests; awesome-mcp-servers directs submissions through its website and does not accept pull requests.
- awesome-agent-skills is licensed CC0-1.0 and lists TypeScript as its language; awesome-mcp-servers is licensed MIT.
- awesome-agent-skills reports 20 stars and 61 forks; awesome-mcp-servers reports 4.3k stars and 2.1k forks.
Choose awesome-agent-skills if you…
- need to compare agent resources across multiple platforms and formats.
- want to browse skills, editor rules, framework tools, and discovery or installation options in one index.
- prefer a directory that accepts community contributions through pull requests.
Choose awesome-mcp-servers if you…
- need to find MCP servers for connecting AI clients to services, tools, or data sources.
- want to compare reference, official, and community MCP server listings.
- are exploring MCP examples, including implementations of tools, prompts, and resources.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.