Content
# 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!
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