Manual setup required. The maintainer's config contains paths only you know - edit the placeholders below before adding it to Claude Code.
1
Prepare the server locally
Run this once before adding it to Claude Code.
git clone https://github.com/JMRussas/ollama-mcp
cd ollama-mcpThen follow the repository README for any remaining dependency or build steps.
2
Register it in Claude Code
claude mcp add ollama-mcp -- python /path/to/src/ollama_mcp/server.pyReplace any placeholder paths in the command with the real path on your machine.
Available Tools (4)
Once configured, Ollama MCP gives your AI agent access to:
ollama_generatePerforms a single-turn prompt to response generation.promptmodelollama_chatFacilitates a multi-turn conversation with the model.messagesmodelollama_embedGenerates embedding vectors for provided text.textmodelollama_list_modelsLists all models currently available on your Ollama instances.Try It Out
After setup, try these prompts with your AI agent:
→List all the models I currently have installed in my local Ollama instance.
→Generate a draft for a README file for my new project using the llama3 model.
→Create an embedding vector for the following text snippet to use in my RAG pipeline.
→Continue our conversation about this code snippet using the mistral model.
Prerequisites & system requirements
- An MCP-compatible client (Claude Code, Cursor, Windsurf, Claude Desktop, or Codex)
- Python 3.8+ with pip installed
Alternative installation methods
Setup Script
bash setup.shConare · memory for coding agents
Keep this setup from going cold
Save the docs, env vars, and workflow around Ollama MCP in Conare so Claude Code, Codex, and Cursor remember it next time.
Remember this setup$npx conare@latest