MCP Ollama Manager Extension

A VS Code extension for managing the MCP Ollama Python server, providing a convenient interface to start, stop, configure and monitor your Ollama MCP server directly from Visual Studio Code.

Features

• 🚀 Server Management: Start, stop, and restart the MCP Ollama server with simple commands
• 📊 Status Monitoring: Real-time server status in the status bar with health checks
• ⚙️ Configuration Management: Easy configuration of server settings through VS Code settings
• 📝 Log Viewing: Built-in output channel for server logs and monitoring
• 🌳 Ollama Models Sidebar: Browse all locally installed models in a dedicated Explorer tree view — visible when the server is running, with a refresh button in the view title
• 🤖 Model Management: Pull, delete, list running models, and view detailed model information
• 💬 AI Tools: Chat with any model, generate text, create embeddings, explain selected code, and write docstrings
• 🔧 Auto-start Option: Configure the server to start automatically with VS Code

Requirements

• MCP Ollama Python installed
• Python 3.7 or higher
• Ollama installed and running

Automatic dependency check: On every VS Code startup the extension silently verifies that mcp-ollama-python is installed. If it is missing a warning notification appears with an Install Now button that runs pip install mcp-ollama-python and streams output to the MCP Ollama Server output channel.

Installation

From VS Code Marketplace

1. Open VS Code
2. Go to Extensions (Ctrl+Shift+X)
3. Search for "MCP Ollama Manager"
4. Click Install

From Source

1. Clone this repository
2. Install dependencies: npm install
3. Compile: npm run compile
4. Package: npm run package
5. Install the resulting .vsix file using code --install-extension mcp-ollama-extension-*.vsix

Or upgrade:

1. Uninstall the old version (optional but recommended) code --uninstall-extension internetics.mcp-ollama-extension

2. Install the new VSIX code --install-extension mcp-ollama-extension-1.0.1.vsix

Configuration

The extension can be configured through VS Code settings. Open settings (Ctrl+,) and search for "MCP Ollama".

Important: Configure Ollama Hostname

If your Ollama server is running on a different hostname (not localhost), you must configure it:

1. Open VS Code Settings (Ctrl+,)
2. Search for "MCP Ollama"
3. Set "Mcp-ollama: Server Host" to your Ollama hostname (e.g., ai, 192.168.1.100, etc.)

The extension will connect to Ollama at http://{serverHost}:11434

Example configurations:

• Local Ollama: localhost (default)
• Network hostname: ai
• IP address: 192.168.1.100

OLLAMA_HOST environment variable: When mcp-ollama.serverHost is empty the extension automatically falls back to the OLLAMA_HOST environment variable. The Configure Server → Ollama Host dialog always pre-fills with the effective resolved value (setting → OLLAMA_HOST → localhost) so you never see a blank field.

Settings

Commands

All commands are available in the Command Palette (Ctrl+Shift+P) under the MCP Ollama category.

Server

Models

AI Tools

Usage

First Time Setup

1. Install the extension
2. Open the Command Palette (Ctrl+Shift+P)
3. Run "MCP Ollama: Configure Server"
4. Select "Configure Server Path" and choose your mcp-ollama-python installation directory
5. Configure other settings as needed (port, log level, etc.)

Starting the Server

• Use the command "MCP Ollama: Start Server" or
• Click the status bar item "MCP Ollama" or
• Enable auto-start in settings

Monitoring

• The status bar shows the server status (🟢 running, 🔴 stopped)
• View real-time logs with "MCP Ollama: View Server Logs"
• Check server status with "MCP Ollama: Show Server Status"

Managing Models

The Ollama Models view appears in the Explorer sidebar whenever the server is running.

• Each entry shows the model name and its size on disk
• Hover over an entry for the full digest and last-modified date
• Click the $(refresh) Refresh icon in the view title to reload the list
• The list clears automatically when the server stops

You can also manage models via the Command Palette:

• Pull Model — prompts for a model name (e.g. llama3.2) and downloads it; the sidebar refreshes on completion
• Delete Model — select from installed models; asks for confirmation before deleting; sidebar refreshes on completion
• List Running Models — shows which models are currently loaded in GPU/CPU memory and their VRAM usage
• Show Model Details — opens a Markdown document with the full model metadata (architecture, parameters, quantization, etc.)

Development

Prerequisites

# Install dependencies
npm install

Building for Development

Development builds are optimized for fast compilation and debugging:

# Compile TypeScript (development mode)
npm run compile

# Watch mode - automatically recompile on file changes
npm run watch

Development build features:

• Fast compilation with transpileOnly mode (3-5x faster)
• Detailed source maps (eval-source-map) for better debugging
• No minification for readable output
• Verbose webpack logging
• Filesystem caching for faster rebuilds (50-80% faster)

Building for Production

Production builds are optimized for size and performance:

# Build for production (cross-platform)
npm run build:prod

# Package as VSIX for distribution
npm run package

Note: The build scripts use cross-env for cross-platform compatibility (works on Windows PowerShell, CMD, Linux, and macOS).

Production build features:

• Full TypeScript type checking
• Minification (40-60% smaller bundles)
• Optimized source maps (separate files)
• Deterministic module IDs for better caching
• Tree-shaking to remove unused code
• Single-bundle output (required for VS Code extensions)

Build Comparison

Quick Commands

# Development workflow
npm install              # Install dependencies
npm run watch            # Start watch mode for development

# Production workflow
npm install              # Install dependencies
npm run build:prod       # Build for production
npm run package          # Create VSIX package

# Install locally
code --install-extension mcp-ollama-extension-*.vsix

Testing

# Run tests
npm test

# Run in watch mode
npm run watch-tests

Debugging

1. Open the project in VS Code
2. Press F5 to launch a new VS Code instance with the extension
3. Use the debugger to set breakpoints and debug the extension
4. Check the Debug Console for logs and errors
5. Use "MCP Ollama: View Server Logs" to see server output

Debug Tips:

• Development builds include detailed source maps for accurate debugging
• Use logger.debug() for verbose logging (set log level to 'debug')
• The extension logs are stored in VS Code's log directory
• Server logs are available in the output channel

Changelog

See CHANGELOG.md for full release history.

Support

• Report issues on GitHub Issues
• Check the documentation for detailed guides
• Join GitHub Discussions for questions and suggestions

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

MIT License - see LICENSE file for details.

Related Projects

• MCP Ollama Python - The Python MCP server for Ollama
• Ollama - Get up and running with large language models locally

Note: This extension requires the MCP Ollama Python server to be installed separately. Please refer to the MCP Ollama Python documentation for installation instructions.