Which integrations are available for this server?

Exposes local Ollama instances to provide capabilities for single-turn text generation, multi-turn chat conversations, embedding vector generation, and management of local models.

How do I use Ollama MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Ollama MCP Server generate a unit test for this function using llama3" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

ollama-mcp

An MCP (Model Context Protocol) server that exposes local Ollama instances as tools for Claude Code.

Lets Claude offload code generation, drafts, embeddings, and quick questions to your local GPUs.

Setup

Run the setup script:
```
bash setup.sh
```
This creates a venv, installs dependencies, generates a machine-specific config.json, and registers the MCP server with Claude Code.
Note: setup.sh uses cygpath and targets Windows (Git Bash / MSYS2). On Linux/macOS, replace the cygpath -w calls with the paths directly, or register manually:
claude mcp add ollama -s user -- /path/to/.venv/bin/python /path/to/src/ollama_mcp/server.py
Restart Claude Code.

Tools

Tool	Description
`ollama_generate`	Single-turn prompt → response
`ollama_chat`	Multi-turn conversation
`ollama_embed`	Generate embedding vectors
`ollama_list_models`	List models on your Ollama instances

Configuration

Copy config.example.json to config.json and fill in your machine details, or let setup.sh generate it interactively.

Requirements

Python 3.10+
Ollama 0.4.0+ running on at least one machine
Claude Code with MCP support

Development

pip install -e ".[dev]"
pytest tests/ -v

About

Extracted from a private developer infrastructure repo and published as a standalone tool. This server runs daily as part of a multi-project AI development workflow spanning game engines, RAG pipelines, and task orchestration — see mcp-rag and orchestration-engine for projects that use it.

Troubleshooting

Problem	Cause	Fix
`config.json not found`	Setup not run	Run `bash setup.sh`
404 on embed calls	Ollama < 0.4.0	Upgrade Ollama (`ollama update`)
`Cannot connect to...`	Ollama not running on target host	Start Ollama: `ollama serve` or check Docker
`Request timed out`	Large model / slow hardware	Increase `timeout` in config.json, or pass `timeout` parameter
`OFFLINE` in list_models	Host unreachable	Check network, firewall, Ollama port 11434
`cygpath: command not found`	Running setup.sh on Linux/macOS	See setup note above