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Context Awesome

作者:bh-rat版本 0.1.1i★ –i电脑或云端
注册名称io.github.bh-rat/context-awesome

安装

概览

作者提供的说明(英文原文)

MCP server for accessing curated awesome list documentation

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

  • 在云端运行无需安装任何东西,通过互联网连接
  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://www.context-awesome.com/api/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "context-awesome": {
      "command": "npx",
      "args": [
        "-y",
        "context-awesome"
      ]
    }
  }
}

在终端中运行这条命令

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

或者在你的电脑上运行

claude mcp add context-awesome -- npx -y context-awesome

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

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

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "context-awesome": {
      "command": "npx",
      "args": [
        "-y",
        "context-awesome"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "context-awesome": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "context-awesome"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://www.context-awesome.com/api/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 bh-rat 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32712 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32712 个服务器的 12% 更新
  • 基础检查结果等于或优于此分类中其他 32712 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Context Awesome 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.1)于5个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Aiterm MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Aiterm MCP

作者:kitepon

Persistent terminals and one launcher for Claude, Codex, Grok, Cursor, and Antigravity harnesses.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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 :

  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

Two Ways to Use Context Awesome

ModeInstallGood for
MCP Serverpoint your agent at the hosted URL or spawn context-awesome-mcpClaude Desktop, Cursor, Windsurf, VS Code — agents that natively speak MCP
CLInpm install -g context-awesomeScripts, shell workflows, editors without MCP support, CI jobs

Both modes ship from the same npm package (context-awesome) and hit the same hosted backend.

MCP Tools

Every MCP tool has a 1:1 CLI subcommand — the server and the CLI expose the same operations.

ToolCLI equivalentWhat it does
find_awesome_sectioncontext-awesome sections Discover sections/categories across awesome lists matching a query
search_awesome_itemscontext-awesome search Full-text search across individual items (tools/libraries/resources)
get_awesome_itemscontext-awesome items Fetch items from a known list + section, token-budgeted

CLI Commands

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 Find sections matching a query search Search items (e.g., context-awesome search "postgres orm") items Fetch items from a list (by owner/repo or listId)

Globals: --api-host Backend API host (env: CONTEXT_AWESOME_API_HOST) --api-key API key (env: CONTEXT_AWESOME_API_KEY) --json Emit raw JSON (for scripts)

Install the CLI
npm install -g context-awesome

context-awesome --help context-awesome search "rate limiter" context-awesome sections "graph databases"

Use the CLI without installing
npx context-awesome search "vector database"

Installation — MCP Clients

Remote Server (Recommended)

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

Install in Cursor

Go to: Settings → Cursor Settings → MCP → Add new global MCP server

{

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

Install in Claude Code

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

Install in Claude Desktop

Settings → Connectors → Add Custom Connector.

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

Install in Windsurf / VS Code / Zed / JetBrains / LM Studio / ...

Use 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.

Local stdio (Claude Desktop, offline-capable)
{

"mcpServers": { "context-awesome": { "command": "npx", "args": ["-y", "context-awesome-mcp", "serve", "--transport", "stdio"], "env": { "CONTEXT_AWESOME_API_HOST": "https://api.context-awesome.com" } } } }

Local HTTP transport (for custom integrations)
npx context-awesome-mcp serve --transport http --port 3001

then point your client at http://localhost:3001/mcp

Local Development

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

Backend service

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.

Additional Installation Methods

Install in Cline

{

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

Install in Zed

{

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

Install in Augment Code

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

Install in Roo Code

{

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

Install in Gemini CLI

{

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

Install in Opencode

"mcp": {

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

Install in JetBrains AI Assistant

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

Install in Kiro

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

Install in Trae

{

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

Install in Amazon Q Developer CLI

{

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

Install in Warp

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

Install in Copilot Coding Agent

{

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

Install in LM Studio

  1. Navigate to Program > Install > Edit mcp.json
  2. Add:
{

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

Install in BoltAI

{

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

Install in Perplexity Desktop

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

Install in Visual Studio 2022

{

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

Install in Crush

{

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

Install in Rovo Dev CLI

acli rovodev mcp

Then add:

{

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

Install in Zencoder

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

Install in Qodo Gen

  1. Open Qodo Gen chat panel
  2. Click Connect more tools
  3. Click + Add new MCP
  4. Add:
{

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

License

MIT

Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Add tests for new functionality
  4. Ensure all tests pass
  5. Submit a pull request

Support

For issues and questions:

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:

问 PopNx