context-awesome

[](https://modelcontextprotocol.io)

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 :

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

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

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"

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 filte