Local AI with Ollama, WebUI & MCP on Windows

A self-hosted AI stack combining Ollama for running language models, Open WebUI for user-friendly chat interaction, and MCP for centralized model management—offering full control, privacy, and flexibility without relying on the cloud.

This sample project provides an MCP-based tool server for managing employee leave balance, applications, and history. It is exposed via OpenAPI using mcpo for easy integration with Open WebUI or other OpenAPI-compatible clients.

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🚀 Features

• ✅ Check employee leave balance
• 📆 Apply for leave on specific dates
• 📜 View leave history
• 🙋 Personalized greeting functionality

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📁 Project Structure

leave-manager/
├── main.py                  # MCP server logic for leave management
├── requirements.txt         # Python dependencies for the MCP server
├── Dockerfile               # Docker image configuration for the leave manager
├── docker-compose.yml       # Docker Compose file to run leave manager and Open WebUI
└── README.md                # Project documentation (this file)

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📋 Prerequisites

1. Windows 10 or later (required for Ollama)
2. Docker Desktop for Windows (required for Open WebUI and MCP)
   • Install from: Docker Desktop for Windows

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🛠️ Workflow

1. Install Ollama on Windows
2. Pull the deepseek-r1 model
3. Clone the repository and navigate to the project directory
4. Run the docker-compose.yml file to launch services

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Install Ollama

➤ Windows

1. Download the Installer:

   • Visit Ollama Download and click Download for Windows to get OllamaSetup.exe.
   • Alternatively, download from Ollama GitHub Releases.

2. Run the Installer:

   • Execute OllamaSetup.exe and follow the installation prompts.
   • After installation, Ollama runs as a background service, accessible at: http://localhost:11434.
   • Verify in your browser; you should see:

     Ollama is running
     

   

3. Start Ollama Server (if not already running):

   ollama serve
   

   • Access the server at: http://localhost:11434.

Verify Installation

Check the installed version of Ollama:

ollama --version

Expected Output:

ollama version 0.7.1

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Pull the deepseek-r1 Model

1. Pull the Default Model (7B):

Using PoweShell

ollama pull deepseek-r1

To Pull Specific Versions:

ollama run deepseek-r1:1.5b
ollama run deepseek-r1:671b

2. List Installed Models:

ollama list

Expected:

Expected Output:

NAME                    ID              SIZE
deepseek-r1:latest      xxxxxxxxxxxx    X.X GB

4. Alternative Check via API:

curl http://localhost:11434/api/tags

Expected Output: A JSON response listing installed models, including deepseek-r1:latest.

4. Test the API via PowerShell:

Invoke-RestMethod -Uri http://localhost:11434/api/generate -Method Post -Body '{"model": "deepseek-r1", "prompt": "Hello, world!", "stream": false}' -ContentType "application/json"

Expected Response: A JSON object containing the model's response to the "Hello, world!" prompt.

5. Run and Chat the Model via PowerShell:

ollama run deepseek-r1

• This opens an interactive chat session with the deepseek-r1 model.
• Type /bye and press Enter to exit the chat session.

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🐳 Run Open WebUI and MCP Server with Docker Compose

1. Clone the Repository:

   git clone https://github.com/ahmad-act/Local-AI-with-Ollama-Open-WebUI-MCP-on-Windows.git
   cd Local-AI-with-Ollama-Open-WebUI-MCP-on-Windows
   

2. To launch both the MCP tool and Open WebUI locally (on Docker Desktop):

   docker-compose up --build
   

   

This will:

• Start the Leave Manager (MCP Server) tool on port 8000
• Launch Open WebUI at http://localhost:3000

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🌐 Add MCP Tools to Open WebUI

The MCP tools are exposed via the OpenAPI specification at: http://localhost:8000/openapi.json.

1. Open http://localhost:3000 in your browser.
2. Click the Profile Icon and navigate to Settings.
3. Select the Tools menu and click the Add (+) Button.
4. Add a new tool by entering the URL: http://localhost:8000/.

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💬 Example Prompts

Use these prompts in Open WebUI to interact with the Leave Manager tool:

• Check Leave Balance:

  Check how many leave days are left for employee E001
  

  
• Apply for Leave:

  Apply
  ![exist chat](https://github.com/ahmad-act/Local-AI-with-Ollama-Open-WebUI-MCP-on-Windows/blob/main/readme-img/add-mcp-tools-on-open-webui-12.png)
  

• View Leave History:

  What's the leave history of E001?
  

  
• Personalized Greeting:

  Greet me as Alice
  

  

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🛠️ Troubleshooting

• Ollama not running: Ensure the service is active (ollama serve) and check http://localhost:11434.
• Docker issues: Verify Docker Desktop is running and you have sufficient disk space.
• Model not found: Confirm the deepseek-r1 model is listed with ollama list.
• Port conflicts: Ensure ports 11434, 3000, and 8000 are free.

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📚 Additional Resources

• Ollama Documentation
• Open WebUI Documentation
• Docker Desktop Documentation
• MCP Documentation
• OpenAPI Tool Servers
• mcpo - Works with OpenAPI tools, SDKs, and UIs