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.
claude mcp add --transport http context-awesome https://www.context-awesome.com/api/mcpRun in your terminal. Add --scope user to make it available in every project.
Review the command, arguments, and environment values before installing — MCP servers run with your local permissions.
Verified live against the running server on Jun 10, 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 paramsDiscovers 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...
limitnumberquery*stringconfidencenumberget_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 paramsRetrieves 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.
listIdstringoffsetnumbertokensnumbersectionstringgithubRepostringsubcategorystringA 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 :
https://github.com/user-attachments/assets/babab991-e4ff-4433-bdb7-eb7032e9cd11
| Mode | Install | Good for |
|---|---|---|
| MCP Server | point your agent at the hosted URL or spawn context-awesome-mcp | Claude Desktop, Cursor, Windsurf, VS Code — agents that natively speak MCP |
| CLI | npm install -g context-awesome | Scripts, shell workflows, editors without MCP support, CI jobs |
Both modes ship from the same npm package (context-awesome) and hit the same hosted backend.
Every MCP tool has a 1:1 CLI subcommand — the server and the CLI expose the same operations.
| Tool | CLI equivalent | What it does |
|---|---|---|
find_awesome_section | context-awesome sections <query...> | Discover sections/categories across awesome lists matching a query |
search_awesome_items | context-awesome search <query...> | Full-text search across individual items (tools/libraries/resources) |
get_awesome_items | context-awesome items <target> | Fetch items from a known list + section, token-budgeted |
The CLI (context-awesome) talks directly to the hosted backend. For the MCP server, use the separate context-awesome-mcp binary (see Installation — MCP Clients below).
context-awesome <command> [options]
Commands:
sections <query...> Find sections matching a query
search <query...> Search items (e.g., context-awesome search "postgres orm")
items <target> Fetch items from a list (by owner/repo or listId)
Globals:
--api-host <url> Backend API host (env: CONTEXT_AWESOME_API_HOST)
--api-key <key> API key (env: CONTEXT_AWESOME_API_KEY)
--json Emit raw JSON (for scripts)
npm install -g context-awesome
context-awesome --help
context-awesome search "rate limiter"
context-awesome sections "graph databases"
npx context-awesome search "vector database"
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
Settings → Connectors → Add Custom Connector.
Context Awesomehttps://www.context-awesome.com/api/mcpUse the same URL (https://www.context-awesome.com/api/mcp) with each client's "add remote MCP" UI. See the dedicated sections below for exact snippets.
{
"mcpServers": {
"context-awesome": {
"command": "npx",
"args": ["-y", "context-awesome-mcp", "serve", "--transport", "stdio"],
"env": {
"CONTEXT_AWESOME_API_HOST": "https://api.context-awesome.com"
}
}
}
}
npx context-awesome-mcp serve --transport http --port 3001
# then point your client at http://localhost:3001/mcp
git clone https://github.com/bh-rat/context-awesome.git
cd context-awesome
npm install
npm run build
# CLI
./build/cli.js search "graph databases"
# MCP server (stdio)
./build/index.js --transport stdio
# MCP Inspector
npm run inspector
This MCP server and CLI connect 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.
{
"mcpServers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
{
"context_servers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
https://www.context-awesome.com/api/mcp{
"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
}
}
Settings -> Tools -> AI Assistant -> Model Context Protocol (MCP)+ Addhttps://www.context-awesome.com/api/mcpOK and ApplyKiro > MCP Servers+ Addhttps://www.context-awesome.com/api/mcpSave{
"mcpServers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
{
"mcpServers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
Settings > AI > Manage MCP servers+ Addhttps://www.context-awesome.com/api/mcpSave{
"mcpServers": {
"context-awesome": {
"type": "http",
"url": "https://www.context-awesome.com/api/mcp",
"tools": ["find_awesome_section", "search_awesome_items", "get_awesome_items"]
}
}
}
Program > Install > Edit mcp.json{
"mcpServers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
{
"mcpServers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
Perplexity > SettingsConnectorsAdd ConnectorAdvancedContext Awesomehttps://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"
}
}
}
Context Awesomehttps://www.context-awesome.com/api/mcp{
"mcpServers": {
"context-awesome": {
"url": "https://www.context-awesome.com/api/mcp"
}
}
}
MIT
Contributions are welcome! Please:
For issues and questions:
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.
Built with: