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.

- 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

- Pull models from registries
- Push models to registries
- List available models
- Create custom models from Modelfiles
- Copy and remove models

- Run models with customizable prompts
- Chat completion API with system/user/assistant roles
- Configurable parameters (temperature, timeout)
- Raw mode support for direct responses

- Start and manage Ollama server
- View detailed model information
- Error handling and timeout management

- Ollamainstalled on your system
- Node.js and npm/pnpm

{ "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 } } } }

// 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" } });

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 } });

await mcp.use_mcp_tool({ server_name: "ollama", tool_name: "create", arguments: { name: "custom-model", modelfile: "./path/to/Modelfile" } });

- 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)

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