Leave Manager MCP Tool Server

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.

🚀 Features

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

📁 Project Structure

📋 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

🛠️ 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

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:

Expected Output:

Pull the deepseek-r1 Model

1. Pull the Default Model (7B):

Using PoweShell

To Pull Specific Versions:

2. List Installed Models:

Expected:

Expected Output:

4. Alternative Check via API:

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

4. Test the API via PowerShell:

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

5. Run and Chat the Model via PowerShell:

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

🐳 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

🌐 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/.

💬 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 
• View Leave History:
  What's the leave history of E001?
  
• Personalized Greeting:
  Greet me as Alice
  

🛠️ 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.

📚 Additional Resources

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