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

# 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-server

# # Global Installation

npm install -g copus-mcp-server

Then run:

copus-mcp-server

# # Local Installation

npm install copus-mcp-server

# Configuration

# # 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:

1. Open VS Code Settings
2. Search for "Cline MCP"
3. 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 keywords
• limit (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 build

# # Running in Development

npm run dev

# # Testing

#  Run the server
npm start

#  In another terminal, test with MCP inspector or your AI platform

# API 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=json
• OpenAPI Spec: https://copus.network/.well-known/openapi.yaml
• AI 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.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

# License

MIT License - see LICENSE for details.

# Support

• Issues: https://github.com/copus-io/copus-mcp-server/issues
• Copus: https://copus.network

Built with love by the Copus team.