Ollama-mcp

# Ollama MCP Server 🚀 A powerful bridge between Ollama and the Model Context Protocol (MCP), enabling seamless integration of Ollama's local LLM capabilities into your MCP-powered applications. ## 🌟 Features ### Complete Ollama Integration - **Full API Coverage**: Access all essential Ollama functionality through a clean MCP interface - **OpenAI-Compatible Chat**: Drop-in replacement for OpenAI's chat completion API - **Local LLM Power**: Run AI models locally with full control and privacy ### Core Capabilities - 🔄 **Model Management** - Pull models from registries - Push models to registries - List available models - Create custom models from Modelfiles - Copy and remove models - 🤖 **Model Execution** - Run models with customizable prompts - Chat completion API with system/user/assistant roles - Configurable parameters (temperature, timeout) - Raw mode support for direct responses - 🛠 **Server Control** - Start and manage Ollama server - View detailed model information - Error handling and timeout management ## 🚀 Getting Started ### Prerequisites - [Ollama](https://ollama.ai) installed on your system - Node.js and npm/pnpm ### Installation 1. Install dependencies: ```bash pnpm install ``` 2. Build the server: ```bash pnpm run build ``` ### Configuration Add the server to your MCP configuration: #### For Claude Desktop: MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json` Windows: `%APPDATA%/Claude/claude_desktop_config.json` ```json { "mcpServers": { "ollama": { "command": "node", "args": ["/path/to/ollama-server/build/index.js"], "env": { "OLLAMA_HOST": "http://127.0.0.1:11434" // Optional: customize Ollama API endpoint } } } } ``` ## 🛠 Usage Examples ### Pull and Run a Model ```typescript // Pull a model await mcp.use_mcp_tool({ server_name: "ollama", tool_name: "pull", arguments: { name: "llama2" } }); // Run the model await mcp.use_mcp_tool({ server_name: "ollama", tool_name: "run", arguments: { name: "llama2", prompt: "Explain quantum computing in simple terms" } }); ``` ### Chat Completion (OpenAI-compatible) ```typescript await mcp.use_mcp_tool({ server_name: "ollama", tool_name: "chat_completion", arguments: { model: "llama2", messages: [ { role: "system", content: "You are a helpful assistant." }, { role: "user", content: "What is the meaning of life?" } ], temperature: 0.7 } }); ``` ### Create Custom Model ```typescript await mcp.use_mcp_tool({ server_name: "ollama", tool_name: "create", arguments: { name: "custom-model", modelfile: "./path/to/Modelfile" } }); ``` ## 🔧 Advanced Configuration - `OLLAMA_HOST`: Configure custom Ollama API endpoint (default: http://127.0.0.1:11434) - Timeout settings for model execution (default: 60 seconds) - Temperature control for response randomness (0-2 range) ## 🤝 Contributing Contributions are welcome! Feel free to: - Report bugs - Suggest new features - Submit pull requests ## 📝 License MIT License - feel free to use in your own projects! --- Built with ❤️ for the MCP ecosystem