Skip to main content
Glama
ahmad-act

Leave Manager MCP Tool Server

by ahmad-act

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 managementβ€”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.


πŸš€ Features

  • βœ… Check employee leave balance

  • πŸ“† Apply for leave on specific dates

  • πŸ“œ View leave history

  • πŸ™‹ Personalized greeting functionality


Related MCP server: Lark MCP Server

πŸ“ Project Structure

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

πŸ“‹ Prerequisites

  1. Windows 10 or later (required for Ollama)

  2. Docker Desktop for Windows (required for Open WebUI and MCP)


πŸ› οΈ 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

➀ Windows

  1. Download the Installer:

  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

    Ollama Initial Window Ollama Setup Progress Ollama In System Tray Ollama On Browser

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

    ollama serve

Verify Installation

Check the installed version of Ollama:

ollama --version

Expected Output:

ollama version 0.7.1

Pull the deepseek-r1 Model

1. Pull the Default Model (7B):

Using PoweShell

ollama pull deepseek-r1

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

deepseek-r1:latest

4. Alternative Check via API:

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

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

alternative check

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.

test the API

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.

run and chat

run and chat with Hi

exist chat


🐳 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

    exist chat exist chat exist chat exist chat exist chat exist chat exist chat

This will:


🌐 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. exist chat

  3. Select the Tools menu and click the Add (+) Button. exist chat

  4. Add a new tool by entering the URL: http://localhost:8000/. exist chat exist chat exist chat exist chat exist chat exist chat exist chat


πŸ’¬ 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

    exist chat exist chat

  • Apply for Leave:

    Apply
    ![exist chat](readme-img/add-mcp-tools-on-open-webui-12.png)
  • View Leave History:

    What's the leave history of E001?

    exist chat

  • Personalized Greeting:

    Greet me as Alice

    exist chat


πŸ› οΈ 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.


πŸ“š Additional Resources

-
security - not tested
F
license - not found
-
quality - not tested

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ahmad-act/Local-AI-with-Ollama-Open-WebUI-MCP-on-Windows'

If you have feedback or need assistance with the MCP directory API, please join our Discord server