Agent-Leaderboard
🏆 AI Agent 生态排行榜:Skills · MCP 服务器 · Prompt 库 · 框架 · 深度研究,按 GitHub Stars 每日更新 | Leaderboard for AI agent ecosystem — Skills, MCP, Prompts, Frameworks & Research.
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README
From the repo.
Agent Leaderboard
The go-to leaderboard for discovering trending AI agent ecosystem repositories on GitHub — covering Agent Skills, MCP Servers, Prompt Libraries, AI Frameworks, and Auto Research tools, all ranked by GitHub stars and updated automatically.
Five Boards, One Place
| Board | Repos Tracked | What It Covers |
|---|---|---|
| 🛠 Agent Skills | 500+ | Installable skills/plugins for Claude Code, Cursor, Copilot, Codex and other AI coding agents |
| 🔌 MCP Servers | 1,500+ | Model Context Protocol servers that extend agent tool-use capabilities |
| 📚 Prompt Library | 1,100+ | Curated system prompts, prompt collections, and prompt engineering guides |
| 🏗 AI Frameworks | 1,200+ | Agent orchestration frameworks, multi-agent platforms, and LLM app scaffolding |
| 🔬 Auto Research | 100+ | Autonomous deep-research agents and AI-powered research tools |
→ Explore all boards at agentskills.media
Top 10 Agent Skills
| # | Repository | Description | Stars | Category |
|---|---|---|---|---|
| 1 | affaan-m/everything-claude-code | The agent harness performance optimization system. Skills, instincts, memory,… | ★ 185,355 | claude |
| 2 | NousResearch/hermes-agent | The agent that grows with you | ★ 154,273 | claude |
| 3 | x1xhlol/system-prompts-and-models-of-ai-tools | FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI… | ★ 137,532 | claude |
| 4 | multica-ai/andrej-karpathy-skills | A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy | ★ 133,529 | claude |
| 5 | mattpocock/skills | Skills for Real Engineers. Straight from my .claude directory. | ★ 88,185 | claude |
| 6 | nextlevelbuilder/ui-ux-pro-max-skill | An AI SKILL that provides design intelligence for building professional UI/UX | ★ 79,571 | claude |
| 7 | bytedance/deer-flow | An open-source long-horizon SuperAgent harness that researches, codes, and creates | ★ 68,076 | other |
| 8 | JuliusBrussee/caveman | 🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens | ★ 61,217 | claude |
| 9 | ComposioHQ/awesome-claude-skills | A curated list of awesome Claude Skills, resources, and tools | ★ 60,260 | claude |
| 10 | safishamsi/graphify | AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI…) | ★ 48,702 | claude |
→ See full Agent Skills ranking at agentskills.media
Top 10 MCP Servers
| # | Repository | Description | Stars | Category |
|---|---|---|---|---|
| 1 | punkpeye/awesome-mcp-servers | A collection of MCP servers | ★ 87,171 | general |
| 2 | sansan0/TrendRadar | AI-driven public opinion & trend monitor with multi-platform data | ★ 57,880 | dev_tools |
| 3 | ChromeDevTools/chrome-devtools-mcp | Chrome DevTools for coding agents | ★ 40,041 | web |
| 4 | microsoft/playwright-mcp | Playwright MCP server | ★ 32,726 | web |
| 5 | github/github-mcp-server | GitHub's official MCP Server | ★ 29,976 | official |
| 6 | modelcontextprotocol/servers | Model Context Protocol Servers (official reference implementations) | ★ — | official |
| 7 | jlowin/fastmcp | The fast, Pythonic way to build MCP servers | ★ — | dev_tools |
| 8 | Cursor-to-API/cursor-api | Use Cursor as an OpenAI-compatible API | ★ — | dev_tools |
| 9 | bgauryy/octocode-mcp | MCP server for semantic code research and context generation | ★ — | dev_tools |
| 10 | PatrickJS/awesome-cursorrules | Configuration files that enhance Cursor AI editor experience | ★ — | general |
→ See full MCP Servers ranking at agentskills.media/#mcp
Top 10 Prompt Libraries
| # | Repository | Description | Stars | Category |
|---|---|---|---|---|
| 1 | f/awesome-chatgpt-prompts | Awesome ChatGPT Prompts — share, discover and collect prompts | ★ 162,535 | collection |
| 2 | x1xhlol/system-prompts-and-models-of-ai-tools | Extracted system prompts from major AI tools | ★ 137,850 | system |
| 3 | dair-ai/Prompt-Engineering-Guide | Guides, papers, and resources for prompt engineering | ★ 74,758 | engineering |
| 4 | PlexPt/awesome-chatgpt-prompts-zh | ChatGPT 中文调教指南 | ★ 60,191 | collection |
| 5 | obra/superpowers | An agentic skills framework & software development methodology | ★ 198,224 | engineering |
| 6 | anthropics/anthropic-cookbook | Recipes and notebooks for using Claude effectively | ★ — | engineering |
| 7 | openai/openai-cookbook | Examples and best practices for working with the OpenAI API | ★ — | engineering |
| 8 | brexhq/prompt-engineering | Tips and tricks for working with Large Language Models | ★ — | engineering |
| 9 | linexjlin/GPTs | Leaked prompts of GPTs | ★ — | system |
| 10 | ai-boost/awesome-prompts | Curated list of awesome ChatGPT prompts | ★ — | collection |
→ See full Prompt Library ranking at agentskills.media/#prompts
Top 10 AI Frameworks
| # | Repository | Description | Stars | Category |
|---|---|---|---|---|
| 1 | obra/superpowers | An agentic skills framework & software development methodology | ★ 198,224 | general |
| 2 | langchain-ai/langchain | The agent engineering platform | ★ 137,134 | orchestration |
| 3 | vllm-project/vllm | High-throughput and memory-efficient inference and serving for LLMs | ★ 80,489 | memory |
| 4 | TauricResearch/TradingAgents | Multi-Agents LLM Financial Trading Framework | ★ 77,314 | multi_agent |
| 5 | FoundationAgents/MetaGPT | The Multi-Agent Framework: First AI Software Company | ★ 68,127 | multi_agent |
| 6 | microsoft/autogen | A programming framework for agentic AI | ★ — | orchestration |
| 7 | crewAIInc/crewAI | Framework for orchestrating role-playing, autonomous AI agents | ★ — | orchestration |
| 8 | pydantic/pydantic-ai | Agent Framework / shim to use Pydantic with LLMs | ★ — | orchestration |
| 9 | BerriAI/litellm | Call all LLM APIs using the OpenAI format | ★ — | routing |
| 10 | openai/swarm | Educational framework for lightweight multi-agent orchestration | ★ — | orchestration |
→ See full AI Frameworks ranking at agentskills.media/#frameworks
Top 10 Auto Research Tools
| # | Repository | Description | Stars | Category |
|---|---|---|---|---|
| 1 | karpathy/autoresearch | AI agents running research on single-GPU nanochat training automatically | ★ 81,483 | general |
| 2 | bytedance/deer-flow | An open-source long-horizon SuperAgent harness that researches, codes, and creates | ★ 68,076 | deep_research |
| 3 | microsoft/qlib | AI-oriented Quant investment platform | ★ 43,098 | literature |
| 4 | 666ghj/BettaFish | 多Agent舆情分析助手,打破信息茧房,还原舆情原貌 | ★ 40,936 | deep_research |
| 5 | khoj-ai/khoj | Your AI second brain. Self-hostable. Get answers from the web or your docs. | ★ 34,578 | deep_research |
| 6 | stanford-oval/storm | An LLM-powered knowledge curation system that researches and generates wiki-like articles | ★ 28,228 | deep_research |
| 7 | assafelovic/gpt-researcher | An autonomous agent that conducts deep research on any data using any LLM | ★ 27,113 | deep_research |
| 8 | mvanhorn/last30days-skill | AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket | ★ 26,015 | deep_research |
| 9 | virattt/dexter | An autonomous agent for deep financial research | ★ 25,789 | data_research |
| 10 | dzhng/deep-research | An AI-powered research assistant that performs iterative, deep research on any topic | ★ 18,924 | deep_research |
→ See full Auto Research ranking at agentskills.media/#research
Features
| Feature | Description |
|---|---|
| 🌐 Five Boards | Agent Skills · MCP Servers · Prompt Library · AI Frameworks · Auto Research |
| 🔍 Multi-filter | Keyword search, language, Stars threshold (All / 500+ / 1k+ / 5k+ / 10k+), time range |
| 🏷️ Use-case chips | Click tags to filter by use case — multi-select with OR logic |
| ⊞ Dual views | Grid / List view toggle, 24 / 48 / 96 items per page |
| ❤️ Favorites | Bookmark repos; persisted in localStorage |
| 🌐 i18n | Switch between English and Chinese with one click |
| 🌙 Theme | Dark mode (default) / Light mode toggle |
| 📊 Auto tagging | Parses repo description + topics to assign use-case labels |
| 📄 Pagination | Smart pagination with ellipsis |
Quick Start
# 1. Clone the repo
git clone https://github.com/jaychempan/Agent-Leaderboard.git
cd Agent-Leaderboard
# 2. Fetch data (Python 3.8+, no extra dependencies)
python3 scripts/fetch_data.py # Agent Skills
python3 scripts/fetch_mcp.py # MCP Servers
python3 scripts/fetch_prompts.py # Prompt Library
python3 scripts/fetch_frameworks.py # AI Frameworks
python3 scripts/fetch_auto_research.py # Auto Research
# Optional: supply a GitHub Token to raise the API rate limit (60 → 5000 req/hr)
python3 scripts/fetch_data.py --token ghp_xxxxxxxxxxxx
# 3. Serve locally
# Option A — with live reload (auto-refreshes browser on file change, requires Node)
npx live-server --port=8080
# Option B — basic static server (no live reload, no extra dependencies)
python3 -m http.server 8080
# then open http://localhost:8080
MCP Skill Discovery
Use the catalog directly from any AI chat client that supports MCP. This Bash command installs the server, creates an isolated venv under ~/.local/share/skills-discovery-mcp, and configures detected clients:
curl -fsSL https://raw.githubusercontent.com/jaychempan/Agent-Leaderboard/main/scripts/install.sh \
| SKILLS_DISCOVERY_CONFIGURE_CLIENTS=auto bash
Use macOS, Linux, WSL, or Git Bash for the installer. Native PowerShell does not support this Bash syntax.
For Codex, verify the server is registered, then start a new Codex session:
codex mcp list
Quick examples are in docs/mcp-quick-use.zh.md.
To skip client config or target specific clients:
SKILLS_DISCOVERY_CONFIGURE_CLIENTS=none bash scripts/install.sh
SKILLS_DISCOVERY_CONFIGURE_CLIENTS=codex,claude,cursor bash scripts/install.sh
The installer backs up config files before editing them. If your client is not configured automatically, add this fallback manually:
{
"mcpServers": {
"skills-discovery": {
"command": "skills-discovery-mcp"
}
}
}
Re-run scripts/install.sh to update an existing install. To uninstall:
curl -fsSL https://raw.githubusercontent.com/jaychempan/Agent-Leaderboard/main/scripts/uninstall.sh | bash
You can also run the server directly from a cloned checkout:
python3 -m mcp.skills_discovery.server
By default the server reads the daily remote catalog at https://agentskills.media/data/discovery_index.json, generated from the leaderboard data. To test a local or custom index, point it at an absolute file URL:
SKILLS_DISCOVERY_INDEX_URL=file:///absolute/path/to/data/discovery_index.json \
python3 -m mcp.skills_discovery.server
Example chat queries:
- Find Codex testing skills
- Recommend Claude UI/UX skills
- Top MCP browser automation servers
The server returns guidance, matching repositories, and links only. It does not execute install commands or modify your environment.
File Structure
agent-leaderboard/
├── index.html # Single-page app (all five boards)
├── favicon.svg # Site logo / favicon
│
├── src/
│ ├── shared.css # Shared styles (dark / light theme)
│ └── shared.js # Shared logic (i18n, filtering, rendering, routing)
│
├── scripts/
│ ├── fetch_data.py # Crawl Skills repos → data/data.js
│ ├── fetch_mcp.py # Crawl MCP repos → data/mcp_data.js
│ ├── fetch_prompts.py # Crawl Prompt repos → data/prompts_data.js
│ ├── fetch_frameworks.py # Crawl Framework repos → data/frameworks_data.js
│ ├── fetch_auto_research.py # Crawl Research repos → data/auto_research_data.js
│ ├── build_discovery_index.py # Build MCP discovery index → data/discovery_index.js
│ └── fetch_utils.py # Shared fetch utilities
│
└── data/
├── data.json / data.js # Agent Skills data
├── mcp_data.json / mcp_data.js # MCP Servers data
├── prompts_data.json / prompts_data.js # Prompt Library data
├── frameworks_data.json / frameworks_data.js # AI Frameworks data
├── auto_research_data.json / auto_research_data.js # Auto Research data
└── discovery_index.json / discovery_index.js # Daily MCP discovery index
Automated Updates (GitHub Actions)
Each board has its own daily workflow that keeps data fresh automatically.
| Workflow | Schedule | Board |
|---|---|---|
update-skills.yml | Daily | Agent Skills |
update-mcp.yml | Daily | MCP Servers |
update-prompts.yml | Daily | Prompt Library |
update-frameworks.yml | Daily | AI Frameworks |
update-research.yml | Daily | Auto Research |
weekly-update.yml | On demand | All boards (manual trigger) |
Setup (one-time):
- Go to Settings → Secrets and variables → Actions in your GitHub repo.
- Add a secret named
GH_TOKENwith a Personal Access Token (public repo read access is sufficient). - Push this repo to GitHub. Workflows run on schedule automatically.
You can also trigger a full refresh manually via Actions → Update All (Manual) → Run workflow.
Inclusion Criteria
| Skills | MCP Servers | Prompt Library | AI Frameworks | Auto Research | |
|---|---|---|---|---|---|
| Min stars | ★ 100+ | ★ 50+ | ★ 50+ | ★ 50+ | ★ 100+ |
| Keywords | claude / codex / cursor / copilot / skill | mcp / model context protocol / tool server | prompt / system prompt / chatgpt prompts | langchain / autogen / crewai / framework | deep research / autonomous / literature / RAG |
| Categories | Claude · Codex · Cursor · Copilot · Other | Official · Web · Dev Tools · API · General | Collection · System · Engineering · General | Orchestration · Multi-Agent · Memory · Routing | Deep Research · Web Research · Literature · Data · Knowledge Base |
Tech Stack
- Pure HTML + CSS + JS — no framework, no build step
- Python 3 stdlib only —
urllibonly, nopip installneeded - GitHub REST Search API — public endpoint, token optional
Contributing
PRs welcome to improve search queries, use-case tag rules, or the UI!
Collected info
- ★ 49 stars
- Language: JavaScript
- Source updated: 9/24/2026
Config for your environment
Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.
Tool
OS
Config file: ~/.cursor/mcp.json
{
"mcpServers": {
"mcp-server": {
"url": "{MCP_ENDPOINT_URL}"
}
}
}Paste into mcpServers in the config file. Restart Cursor after saving.
If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.