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Dive AI Agent

by OpenAgentPlatform

AI/AgentsAI AgentLLMMCPDesktop ApplicationOpen Source

Dive is an open-source MCP Host Desktop Application that seamlessly integrates with any LLMs supporting function calling capabilities. It allows users to extend LLMs with powerful tools and personalize AI behavior.

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Last updated: 2025/3/14

Dive AI Agent 🤿 🤖

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Dive is an open-source MCP Host Desktop Application that seamlessly integrates with any LLMs supporting function calling capabilities. ✨

Dive Demo

Dive Demo

Features 🎯

  • 🌐 Universal LLM Support: Compatible with ChatGPT, Anthropic, Ollama and OpenAI-compatible models
  • 💻 Cross-Platform: Available for Windows, MacOS, and Linux
  • 🔄 Model Context Protocol: Enabling seamless MCP AI agent integration on both stdio and SSE mode
  • 🌍 Multi-Language Support: Traditional Chinese, Simplified Chinese, English, Spanish with more coming soon
  • ⚙️ Advanced API Management: Multiple API keys and model switching support
  • 💡 Custom Instructions: Personalized system prompts for tailored AI behavior
  • 🔄 Auto-Update Mechanism: Automatically checks for and installs the latest application updates

Recent updates(2025/3/14)

  • 🌍 Spanish Translation: Added Spanish language support
  • 🤖 Extended Model Support: Added Google Gemini and Mistral AI models integration

Download and Install ⬇️

Get the latest version of Dive:

Download

Download

For Windows users: 🪟

  • Download the .exe version
  • Python and Node.js environments are pre-installed

For MacOS users: 🍎

  • Download the .dmg version
  • You need to install Python and Node.js (with npx uvx) environments yourself
  • Follow the installation prompts to complete setup

For Linux users: 🐧

  • Download the .AppImage version
  • You need to install Python and Node.js (with npx uvx) environments yourself
  • For Ubuntu/Debian users:
    • You may need to add --no-sandbox parameter
    • Or modify system settings to allow sandbox
    • Run chmod +x to make the AppImage executable

MCP Tips

While the system comes with a default echo MCP Server, your LLM can access more powerful tools through MCP. Here's how to get started with two beginner-friendly tools: Fetch and Youtube-dl.

Set MCP

Set MCP

Quick Setup

Add this JSON configuration to your Dive MCP settings to enable both tools:

 "mcpServers":{
    "fetch": {
      "command": "uvx",
      "args": [
        "mcp-server-fetch",
        "--ignore-robots-txt"
      ],
      "enabled": true
    },
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/files"
      ],
      "enabled": true
    },
    "youtubedl": {
      "command": "npx",
      "args": [
        "@kevinwatt/yt-dlp-mcp"
      ],
      "enabled": true
    }
  }

Using SSE Server for MCP

You can also connect to an external MCP server via SSE (Server-Sent Events). Add this configuration to your Dive MCP settings:

{
  "mcpServers": {
    "MCP_SERVER_NAME": {
      "enabled": true,
      "transport": "sse",
      "url": "YOUR_SSE_SERVER_URL"
    }
  }
}

Additional Setup for yt-dlp-mcp

yt-dlp-mcp requires the yt-dlp package. Install it based on your operating system:

Windows
winget install yt-dlp
MacOS
brew install yt-dlp
Linux
pip install yt-dlp

Build 🛠️

See BUILD.md for more details.

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