Context Awesome

bh-rat/context-awesome

Gives your AI agent access to 8,500+ curated awesome lists from GitHub, totaling over a million vetted tools, libraries, and resources. Exposes three operations: find_awesome_section to discover categories across lists, search_awesome_items for full-text search of individual entries, and get_awesome_items to pull token-budgeted results from specific lists. Available as both a hosted remote server and a local CLI. Useful when you want your agent to recommend battle-tested libraries instead of guessing, or when doing research that needs high-quality starting points. The backend handles all the list indexing and search, so you just point at the API and start querying.

GitHub stars: 61
tools: 2
transport: STDIO, HTTP
last updated: Jun 10, 2026

View on GitHub

Install

From registry metadata

$ npx add-mcp https://www.context-awesome.com/api/mcp --name context-awesome

Run in your terminal. add-mcp asks which agents to add it to (Claude Code, Codex, Cursor and more). Add -g to install it for every project.

Review the command, arguments and environment values before installing. MCP servers run with your local permissions.

Other ways

Claude Code

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

Run in your terminal. Add --scope user to make it available in every project.

Tools

Verified live · 2 tools

Verified live against the running server on Nov 6, 2026.

find_awesome_sectionDiscovers sections/categories across awesome lists matching a search query and returns matching sections from awesome lists. You MUST call this function before 'get_awesome_items' to discover available sections UNLESS the user explicitly provides a githubRepo or listId. Select...3 params

Discovers sections/categories across awesome lists matching a search query and returns matching sections from awesome lists. You MUST call this function before 'get_awesome_items' to discover available sections UNLESS the user explicitly provides a githubRepo or listId. Select...

Parameters* required

confidencenumber

Minimum confidence score (0-1)default: 0.3

limitnumber

Maximum sections to returndefault: 10

query*string

Search terms for finding sections across awesome lists

get_awesome_itemsRetrieves items from a specific awesome list or section with token limiting. You must call 'find_awesome_section' first to discover available sections, UNLESS the user explicitly provides a githubRepo or listId.6 params

Retrieves items from a specific awesome list or section with token limiting. You must call 'find_awesome_section' first to discover available sections, UNLESS the user explicitly provides a githubRepo or listId.

Parameters* required

githubRepostring

GitHub repo path (e.g., 'sindresorhus/awesome') from find_awesome_section results

listIdstring

UUID of the list (from find_awesome_section results)

offsetnumber

Pagination offset for retrieving more itemsdefault: 0

sectionstring

Category/section name to filter

subcategorystring

Subcategory to filter

tokensnumber

Maximum number of tokens to return (default: 10000). Higher values provide more items but consume more tokens.

Readme

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

Two Ways to Use Context Awesome

View the full README on GitHub

Details

Repository: github.com/bh-rat/context-awesome
Website: www.context-awesome.com
Package: context-awesome
Transport: STDIO, HTTP
Registry: MCP registry, active
Tools verified: Nov 6, 2026