Context Awesome

Give your AI agents access to 8,500+ awesome lists with over 1 million curated resources.

What are Awesome Lists?
Community-curated collections of the best tools, libraries, and resources on any topic - from ML frameworks to design tools. This MCP server lets your agents recommend high-quality, vetted resources instead of random search results.

Demo: Using Context Awesome with Claude to find machine learning resources

8,500+

Awesome Lists

1M+

Curated Resources

850+

What is Context Awesome?

Context Awesome is a Model Context Protocol (MCP) server that provides instant access to the entire awesome lists ecosystem on GitHub. It enables AI agents to discover and retrieve high-quality, community-curated resources across any domain.

✓Search across 8,500+ awesome lists with semantic understanding
✓1mn+ awesome curated resources.
✓Direct integration with Claude, Cursor, and VS Code
✓Token-optimized responses for efficient context usage

Installation

Quick Setup (Hosted Server)

Context Awesome is available as a hosted MCP server. No installation required! Just add the configuration to your MCP client:

Cursor

Settings → Cursor Settings → MCP → Add new global MCP server

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Claude Code

Run in terminal:

claude mcp add --transport http context-awesome https://www.context-awesome.com/api/mcp

Windsurf

Add to MCP config:

{
  "mcpServers": {
    "context-awesome": {
      "serverUrl": "https://www.context-awesome.com/api/mcp"
    }
  }
}

VS Code

Add to settings:

"mcp": {
  "servers": {
    "context-awesome": {
      "type": "http",
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add Custom Connector

• Name: Context Awesome
• URL: https://www.context-awesome.com/api/mcp

See installation for other MCP clients →

Local Installation (For Development)

1. Clone and Build

git clone https://github.com/bh-rat/context-awesome.git
cd context-awesome
npm install
npm run build

2. Configure for Local Use

Add to your MCP client configuration:

{
  "mcpServers": {
    "context-awesome": {
      "command": "node",
      "args": ["/path/to/context-awesome/build/index.js"],
      "env": {
        "CONTEXT_AWESOME_API_HOST": "https://api.context-awesome.com"
      }
    }
  }
}

3. Run the Server

# Default (stdio transport)

npm run start

# HTTP transport

npm run start -- --transport http --port 3001

Available MCP Tools

find_awesome_section

Discovers sections and categories across awesome lists matching your search query.

Parameters: query, confidence, limit

get_awesome_items

Retrieves items from a specific list or section with token limiting for optimal context usage.

Parameters: listId, section, tokens, offset

Example Queries

→ "Find the best machine learning resources for Python"

→ "What are the best resources for authoring technical books?"

→ "Show me testing tools from awesome-rust"

→ "Get React component libraries from awesome lists"

→ "Find database ORMs in Go awesome lists"

Additional Installation Methods

Cline

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Zed

{
  "context_servers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Augment Code

Click hamburger menu
Select Settings → Tools
Click + Add MCP
Enter URL: https://www.context-awesome.com/api/mcp

Roo Code

{
  "mcpServers": {
    "context-awesome": {
      "type": "streamable-http",
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Gemini CLI

{
  "mcpServers": {
    "context-awesome": {
      "httpUrl": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Opencode

"mcp": {
  "context-awesome": {
    "type": "remote",
    "url": "https://www.context-awesome.com/api/mcp",
    "enabled": true
  }
}

JetBrains AI Assistant

Settings → Tools → AI Assistant → MCP
Click + Add
Configure URL: https://www.context-awesome.com/api/mcp

Kiro

Navigate Kiro → MCP Servers
Click + Add
Configure URL: https://www.context-awesome.com/api/mcp

Trae

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Amazon Q Developer CLI

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Warp

Settings → AI → Manage MCP servers
Click + Add
Configure URL: https://www.context-awesome.com/api/mcp

Copilot Coding Agent

{
  "mcpServers": {
    "context-awesome": {
      "type": "http",
      "url": "https://www.context-awesome.com/api/mcp",
      "tools": ["find_awesome_section", "get_awesome_items"]
    }
  }
}

LM Studio

Navigate to Program → Install → Edit mcp.json

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

BoltAI

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Perplexity Desktop

Navigate Settings → Connectors
Click Add Connector → Advanced
Name: Context Awesome
URL: https://www.context-awesome.com/api/mcp

Visual Studio 2022

{
  "inputs": [],
  "servers": {
    "context-awesome": {
      "type": "http",
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Crush

{
  "$schema": "https://charm.land/crush.json",
  "mcp": {
    "context-awesome": {
      "type": "http",
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Rovo Dev CLI

Run: acli rovodev mcp

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

Zencoder

Zencoder menu (...) → Agent tools
Click Add custom MCP
Name: Context Awesome
URL: https://www.context-awesome.com/api/mcp

Qodo Gen

Open chat panel → Connect more tools → + Add new MCP

{
  "mcpServers": {
    "context-awesome": {
      "url": "https://www.context-awesome.com/api/mcp"
    }
  }
}

View on GitHub →