Copus MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Copus MCP ServerFind me some recommended resources for learning Python."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Copus MCP Server
An MCP (Model Context Protocol) server that allows AI assistants to search and retrieve human-curated content recommendations from Copus.
What is Copus?
Copus is a human-curated content discovery platform — "The Internet Treasure Map". Unlike SEO-driven search results, Copus surfaces recommendations from real people who explain why content is valuable.
Each curation includes:
Curator's personal note — Why they recommend this
Curator credentials — Why they're qualified to recommend this
Original source URL — The actual content being recommended
AI-enhanced metadata — Key takeaways, target audience, problem solved
Engagement metrics — Views, saves, comments from the community
Related MCP server: o3-search MCP
What This MCP Server Enables
This server gives AI assistants access to Copus's curated content database. Instead of generic search results, your AI can find:
Tools and resources vetted by domain experts
Articles recommended by practitioners in the field
Hidden gems that real people found valuable enough to share
Compatible AI Platforms
This MCP server works with any AI platform that supports the Model Context Protocol:
Claude Desktop (Anthropic)
Claude Code (Anthropic)
Cursor (AI code editor)
Cline (VS Code extension)
Continue (VS Code/JetBrains extension)
Zed (Code editor)
Any other MCP-compatible AI platform
Installation
Quick Start (npx)
No installation required — run directly with npx:
npx copus-mcp-serverGlobal Installation
npm install -g copus-mcp-serverThen run:
copus-mcp-serverLocal Installation
npm install copus-mcp-serverConfiguration
Claude Desktop
Add to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"copus": {
"command": "npx",
"args": ["copus-mcp-server"]
}
}
}Or if installed globally:
{
"mcpServers": {
"copus": {
"command": "copus-mcp-server"
}
}
}Claude Code
Add to your Claude Code MCP settings:
{
"mcpServers": {
"copus": {
"command": "npx",
"args": ["copus-mcp-server"]
}
}
}Cursor
Add to your Cursor MCP configuration (.cursor/mcp.json in your project or global settings):
{
"mcpServers": {
"copus": {
"command": "npx",
"args": ["copus-mcp-server"]
}
}
}Cline (VS Code Extension)
Add to Cline's MCP settings in VS Code:
Open VS Code Settings
Search for "Cline MCP"
Add the server configuration:
{
"copus": {
"command": "npx",
"args": ["copus-mcp-server"]
}
}Continue (VS Code/JetBrains)
Add to your Continue configuration (~/.continue/config.json):
{
"mcpServers": [
{
"name": "copus",
"command": "npx",
"args": ["copus-mcp-server"]
}
]
}Available Tools
search_curations
Search human-curated content recommendations on Copus.
Parameters:
query(string, required): Search keywordslimit(number, optional): Maximum results (default: 10, max: 50)
Returns: Array of curations with:
Title and description
Curator name and profile
Original source URL
Category and keywords
Engagement metrics (views, saves)
get_curation
Get detailed information about a specific curation.
Parameters:
id(string, required): Curation ID (UUID from search results)
Returns: Full curation details including:
Curator's personal recommendation note
Curator credentials
Key takeaways
Target audience
What problem this content solves
Full engagement metrics
Example Use Cases
Once configured, you can ask your AI assistant things like:
Learning Resources
"I want to learn Python, what resources should I check out?"
"Find me some recommended machine learning tutorials"
"What are the best resources for learning web development?"
Tools & Software
"What tools do designers recommend for wireframing?"
"Find me some AI tools that people actually use and recommend"
"What's a good free video editing software?"
Reading & Content
"Any good reads on creative writing?"
"Find me articles about productivity that people found valuable"
"What are some recommended newsletters about tech?"
Specific Topics
"Find watermark remover tools"
"What Linux tools do people recommend?"
"Show me personal growth content recommendations"
Example Response
When you search for "python tutorials", you might get:
{
"query": "python tutorials",
"totalResults": 5,
"results": [
{
"id": "abc123...",
"title": "Real Python - Python Tutorials",
"description": "Comprehensive Python tutorials covering basics to advanced topics...",
"originalSource": "https://realpython.com",
"category": "Technology",
"curator": "experienced_dev",
"engagement": {
"views": 150,
"saves": 23
}
}
]
}Why Use Copus Over Regular Search?
Regular Search | Copus Curations |
SEO-optimized results | Human-selected recommendations |
Algorithm-driven | Expert-vetted content |
No context on quality | Curator explains why it's valuable |
Anonymous sources | Known curator with credentials |
Quantity-focused | Quality-focused |
Development
Building from Source
git clone https://github.com/copus-io/copus-mcp-server.git
cd copus-mcp-server
npm install
npm run buildRunning in Development
npm run devTesting
# Run the server
npm start
# In another terminal, test with MCP inspector or your AI platformAPI Reference
This MCP server wraps the Copus public API:
Search API:
https://copus.network/api/search?q={query}Curation Details:
https://copus.network/work/{id}?format=jsonOpenAPI Spec:
https://copus.network/.well-known/openapi.yamlAI Plugin Manifest:
https://copus.network/.well-known/ai-plugin.json
Links
Copus Website: https://copus.network
Browse Topics: https://copus.network/topics
All Articles: https://copus.network/articles.txt
MCP Protocol: https://modelcontextprotocol.io
MCP TypeScript SDK: https://github.com/modelcontextprotocol/typescript-sdk
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Fork the repository
Create your feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
License
MIT License - see LICENSE for details.
Support
Built with love by the Copus team.
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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