drio
Open app

MCP Servers Multi-Agent AI Infrastructure

Source

Catalog onlyCatalog onlySTDIO

Overview

MCP Servers is a multi-agent AI infrastructure that enables the creation and orchestration of intelligent agents using the Model Context Protocol (MCP). It provides a comprehensive framework for agents to collaborate, share context, and leverage specialized capabilities.

To use MCP Servers, clone the repository from GitHub, set up the Docker network, and start the Qdrant vector database along with the Inspector dashboard for monitoring and debugging agent interactions.

  • Multi-agent collaboration and communication through a standardized protocol. - Semantic search capabilities using vector embeddings. - Modular architecture with components like Inspector and Qdrant-DB. - Real-time monitoring and debugging tools for agent interactions.
  1. Building collaborative multi-agent systems that combine various AI capabilities.
  2. Creating semantic search systems with intuitive AI interfaces.
  3. Extending AI functionalities with specialized tools and data sources.
  4. Development and debugging of MCP servers during the development phase.

Add to your AI client

Use these steps to connect MCP Servers Multi-Agent AI Infrastructure in Cursor, Claude, VS Code, and other MCP-compatible apps. The same JSON appears in the Use with menu above for one-click copy.

Cursor

Add this to your .cursor/mcp.json file in your project root, then restart Cursor.

.cursor/mcp.json

{
  "mcpServers": {
    "mcp-servers-frankgengo": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-servers-frankgengo"
      ]
    }
  }
}

Claude Desktop

Add this server entry to the mcpServers object in your Claude Desktop config, then restart the app.

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

{
  "mcpServers": {
    "mcp-servers-frankgengo": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-servers-frankgengo"
      ]
    }
  }
}

Claude Code

Add this to your project's .mcp.json file. Claude Code will detect it automatically.

.mcp.json (project root)

{
  "mcpServers": {
    "mcp-servers-frankgengo": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-servers-frankgengo"
      ]
    }
  }
}

VS Code (Copilot)

Add this to your .vscode/mcp.json file. Requires the GitHub Copilot extension with MCP support enabled.

.vscode/mcp.json

{
  "servers": {
    "mcp-servers-frankgengo": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-servers-frankgengo"
      ]
    }
  }
}

Windsurf

Add this to your Windsurf MCP config file, then restart Windsurf.

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "mcp-servers-frankgengo": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-servers-frankgengo"
      ]
    }
  }
}

Cline

Open Cline settings, navigate to MCP Servers, and add this server configuration.

Cline MCP Settings (via UI)

{
  "mcpServers": {
    "mcp-servers-frankgengo": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-mcp-servers-frankgengo"
      ]
    }
  }
}

FAQ

What is the Model Context Protocol (MCP)?

MCP is a standardized communication protocol that allows AI agents to share context and capabilities seamlessly.

Is MCP Servers suitable for production use?

Yes, MCP Servers is designed for both development and production environments, providing robust tools for monitoring and debugging.

What technologies are used in MCP Servers?

The project utilizes Docker, Node.js, Python, and various microservices to create a flexible and scalable infrastructure.7:["$","div",null,{"className":"container mx-auto flex flex-col gap-4","children":["$L26","$L27",["$","$L28",null,{"currentProject":{"id":2841,"uuid":"51546e34-f11b-424d-ae78-ebdcd74e0693","name":"mcp-servers","title":"MCP Servers Multi-Agent AI Infrastructure","description":"","avatar_url":"https://avatars.githubusercontent.com/u/87958598?v=4","created_at":"2025-03-15T08:33:44.288Z","updated_at":"2025-03-15T08:44:45.787Z","status":"created","author_name":"FrankGenGo","author_avatar_url":"https://avatars.githubusercontent.com/u/87958598?v=4","tags":"[]","category":"research-and-data","is_featured":false,"sort":1,"url":"https://github.com/FrankGenGo/mcp-servers","target":"_self","content":"$29","summary":"$2a","img_url":null,"type":null,"metadata":"{\"star\":\"0\",\"license\":\"MIT license\",\"language\":\"TypeScript\",\"is_official\":false,\"latest_commit_time\":\"2025-03-18 16:29:38\"}","user_uuid":null,"tools":null,"sse_url":null,"sse_provider":null,"sse_params":null,"is_official":false,"server_command":null,"server_params":null,"server_config":null,"allow_call":false,"is_innovation":false,"is_dxt":false,"dxt_manifest":null,"dxt_file_url":null,"is_audit":false},"randomProjects":[],"currentServerKey":"$undefined"}]]}]

Research and data