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ai-experiments

MCP Tool

donnade6461/ai-experiments

Build a local AI dev stack with OpenWebUI, Ollama, SearXNG, OpenCode, and OpenWork for fast model testing and automation

Install

$ npx loaditout add donnade6461/ai-experiments

Platform-specific configuration:

.claude/settings.json
{
  "mcpServers": {
    "ai-experiments": {
      "command": "npx",
      "args": [
        "-y",
        "ai-experiments"
      ]
    }
  }
}

Add the config above to .claude/settings.json under the mcpServers key.

About

๐Ÿค– ai-experiments - Run Local AI Tools With Ease

[](https://github.com/donnade6461/ai-experiments)

๐Ÿš€ What This Is

ai-experiments is a local AI setup for Windows. It brings together OpenWebUI, Ollama, SearXNG, and OpenCode in one place. You can use it to chat with local models, search the web, and work on coding tasks on your own machine.

This setup focuses on privacy and speed. Your data stays local when possible, and the tools run on your computer instead of a remote service.

๐Ÿ“ฅ Download and Start

Use this link to visit this page to download:

https://github.com/donnade6461/ai-experiments

Steps to get it on Windows
  1. Open the link above in your browser.
  2. Find the latest version or the main project files.
  3. Download the package to your PC.
  4. If the download comes as a ZIP file, right-click it and choose Extract All.
  5. Open the extracted folder.
  6. Look for the start file, such as a .bat file or setup file.
  7. Double-click the file to run it.
  8. If Windows asks for permission, choose Yes.
๐Ÿ–ฅ๏ธ What You Need

This setup works best on a Windows 10 or Windows 11 PC with:

  • 8 GB RAM or more
  • 20 GB of free disk space
  • A modern CPU
  • Internet access for first-time setup and web search
  • A stable power source if you use a laptop

For a smoother experience with local models, 16 GB RAM or more helps.

๐Ÿงฐ What You Get
  • OpenWebUI for a clean chat interface
  • Ollama for running local AI models
  • SearXNG for private web search
  • OpenCode for code work and project tasks
  • A local-first setup for research and development
  • A single environment instead of separate installs
๐Ÿ› ๏ธ How to Install
  1. Download the project from the link above.
  2. Unzip the files if needed.
  3. Open the folder in File Explorer.
  4. Find the install or start file.
  5. Double-click it.
  6. Let Windows finish any

Tags

agentopsaiai-monitoringdata-sciencedata-visualizationdeep-learningembeddingskerasllm-evaluationlstmmachine-learningmcpminingpipelinepredictivepythonrnntextwordwordpress

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Quality Signals

0
Installs
Last updated14 days ago
Security: AREADME

Safety

Risk Levelmedium
Data Access
read
Network Accessnone

Details

Sourcegithub-crawl
Last commit3/30/2026
View on GitHubโ†’

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