context-awesome

context-awesome : awesome references for your agents

A Model Context Protocol (MCP) server that provides access to all the curated awesome lists and their items. It can provide the best resources for your agent from sections of the 8500+ awesome lists on github and more then 1mn+ (growing) awesome row items.

What are Awesome Lists? Awesome lists are community-curated collections of the best tools, libraries, and resources on any topic - from machine learning frameworks to design tools. By adding this MCP server, your AI agents get instant access to these high-quality, vetted resources instead of relying on random web searches.

Perfect for :

Knowledge worker agents to get the most relevant references for their work
The source for the best learning resources
Deep research can quickly gather a lot of high quality resources for any topic.
Search agents

https://github.com/user-attachments/assets/babab991-e4ff-4433-bdb7-eb7032e9cd11

Available Tools

1. `find_awesome_section`

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

Parameters:

query (required): Search terms for finding sections
confidence (optional): Minimum confidence score (0-1, default: 0.3)
limit (optional): Maximum sections to return (1-50, default: 10)

Example Usage: "Give me the best machine learning resources for learning ML related to python in couple of months." "What are the best resources for authoring technical books ?" "Find awesome list sections about React hooks" "Search for database ORMs in Go awesome lists"

2. `get_awesome_items`

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

Parameters:

listId or githubRepo (one required): Identifier for the list
section (optional): Category/section name to filter
subcategory (optional): Subcategory to filter
tokens (optional): Maximum tokens to return (min: 1000, default: 10000)
offset (optional): Pagination offset (default: 0)

Example Usage:

"Show me the testing tools section from awesome-rust"
"Get the next 20 items from awesome-python (offset: 20)"
"Get items from bh-rat/awesome-mcp-enterprise"

Installation

Remote Server (Recommended)

Context Awesome is available as a hosted MCP server. No installation required!

Go to: Settings -> Cursor Settings -> MCP -> Add new global MCP server

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

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

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

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

Navigate to Settings > Connectors > Add Custom Connector. Enter:

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

See Additional Installation Methods for other MCP clients.

Local Setup

For development or self-hosting:

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

Configuration

Running the Server

# Development mode (runs from source)
npm run dev -- [options]

# Production mode (runs compiled version)
npm run start -- [options]

Options:
  --transport <stdio|http|sse>  Transport mechanism (default: stdio)
  --port <number>               Port for HTTP transport (default: 3000)
  --api-host <url>             Backend API host (default: https://api.context-awesome.com)
  --debug                      Enable debug logging
  --help                       Show help

Examples

# Run with default settings (stdio transport)
npm run start

# Run with HTTP transport on port 3001
npm run start -- --transport http --port 3001

# Run with custom API host and key
npm run start -- --api-host https://api.context-awesome.com

MCP Client Configuration

Add to your Claude Desktop configuration file:

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

Add to your settings:

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

For HTTP transport:

npm run start -- --transport http --port 3001 --api-host https://api.context-awesome.com

Then configure your client to connect to http://localhost:3001/mcp

Testing

With MCP Inspector

npm run inspector

Debug Mode

Enable debug logging to see detailed information:

npm run start -- --debug

# Or in development mode
npm run dev -- --debug

Additional Installation Methods

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

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

Click the hamburger menu
Select Settings
Navigate to Tools
Click + Add MCP
Enter URL: https://www.context-awesome.com/api/mcp
Name: Context Awesome

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

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

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

Go to Settings -> Tools -> AI Assistant -> Model Context Protocol (MCP)
Click + Add
Configure URL: https://www.context-awesome.com/api/mcp
Click OK and Apply

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

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

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

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

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

Navigate to Program > Install > Edit mcp.json
Add:

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

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

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

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

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

acli rovodev mcp

Then add:

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

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

Open Qodo Gen chat panel
Click Connect more tools
Click + Add new MCP
Add:

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

Backend service

This MCP server connects to backend API service that handles the heavy lifting of awesome list processing.

The backend service will be open-sourced soon, enabling the community to contribute to and benefit from the complete context-awesome ecosystem.

License

MIT

Contributing

Contributions are welcome! Please:

Fork the repository
Create a feature branch
Add tests for new functionality
Ensure all tests pass
Submit a pull request

Support

For issues and questions:

GitHub Issues: https://github.com/your-org/context-awesome/issues
Documentation: https://docs.context-awesome.com

Attribution

This project uses data from over 8,500 awesome lists on GitHub. See ATTRIBUTION.md for a complete list of all repositories whose data is included.

Credits

Built with:

Model Context Protocol SDK
Awesome Lists
Inspired by context7 MCP server patterns

Deploy Server

HTTP connection URL

security - not tested

license - not found

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Tools

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

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context-awesome

context-awesome : awesome references for your agents

Available Tools

1. `find_awesome_section`

2. `get_awesome_items`

Installation

Remote Server (Recommended)

Local Setup

Configuration

Running the Server

Examples

MCP Client Configuration

Testing

With MCP Inspector

Debug Mode

Additional Installation Methods

Backend service

License

Contributing

Support

Attribution

Credits

Tools

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cognee-mcp

AI Agent Marketplace Index Search

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context-awesome : awesome references for your agents

Available Tools

1. find_awesome_section

2. get_awesome_items

Installation

Remote Server (Recommended)

Local Setup

Configuration

Running the Server

Examples

MCP Client Configuration

Testing

With MCP Inspector

Debug Mode

Additional Installation Methods

Backend service

License

Contributing

Support

Attribution

Credits

Tools

Related MCP Servers

cognee-mcp

AI Agent Marketplace Index Search

Docforkofficial

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New MCP Servers

MCP directory API

1. `find_awesome_section`

2. `get_awesome_items`