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Ollama MCP Server

by etnlbck
npmGitHub
TypeScript
33
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Ollama MCP Server

A Model Context Protocol (MCP) server that provides tools for interacting with Ollama models. This server enables AI assistants to list, chat with, generate responses from, and manage Ollama models through a standardized protocol.

🚀 Features

  • Model Management: List, pull, and delete Ollama models

  • Chat Interface: Multi-turn conversations with models

  • Text Generation: Single-prompt text generation

  • Dual Transport: Stdio (local) and HTTP (remote) support

  • Railway Ready: Pre-configured for Railway deployment

  • Type Safe: Full TypeScript implementation with strict typing

📋 Prerequisites

  • Node.js 18+

  • Ollama installed and running locally

  • For Railway deployment: Railway CLI

🛠️ Installation

Local Development

  1. Clone and install dependencies:

    git clone <repository-url> cd ollama-mcp npm install

  2. Build the project:

    npm run build

  3. Start the server:

    npm start

Using with Cursor

Add this to your Cursor MCP configuration (~/.cursor/mcp/config.json):

{ "mcpServers": { "ollama": { "command": "node", "args": ["/path/to/ollama-mcp/dist/main.js"] } } }

Quick setup:

curl -sSL https://raw.githubusercontent.com/your-repo/ollama-mcp/main/config/mcp.config.json -o ~/.cursor/mcp/config.json

🏗️ Architecture

The project is structured for maximum readability and maintainability:

src/ ├── main.ts # Main entry point ├── config/ # Configuration management ├── server/ # Core MCP server ├── tools/ # MCP tool implementations ├── transports/ # Communication transports └── ollama-client.ts # Ollama API client docs/ # Comprehensive documentation config/ # Configuration files scripts/ # Deployment scripts

See ARCHITECTURE.md for detailed architecture documentation.

🔧 Configuration

Environment Variables

Variable

Description

Default

MCP_TRANSPORT

Transport type (

stdio

or

http

)

stdio

OLLAMA_BASE_URL

Ollama API base URL

http://localhost:11434

MCP_HTTP_HOST

HTTP server host (HTTP mode)

0.0.0.0

MCP_HTTP_PORT

HTTP server port (HTTP mode)

8080

MCP_HTTP_ALLOWED_ORIGINS

CORS allowed origins (HTTP mode)

None

Transport Modes

Stdio Transport (Default)

Perfect for local development and direct integration:

npm start

HTTP Transport

Ideal for remote deployment and web-based clients:

MCP_TRANSPORT=http npm start

🚀 Deployment

Railway Deployment

  1. Install Railway CLI:

    npm install -g @railway/cli railway login

  2. Deploy:

    railway up

  3. Add models (optional):

    railway shell # Follow instructions in docs/RAILWAY_MODELS_SETUP.md

The Railway deployment automatically uses HTTP transport and exposes:

  • MCP Endpoint: https://your-app.railway.app/mcp

  • Health Check: https://your-app.railway.app/healthz

Docker Deployment

# Build the image npm run docker:build # Run locally npm run docker:run # Deploy to Railway railway up

📚 Available Tools

The server provides 5 MCP tools for Ollama interaction:

  1. ollama_list_models - List available models

  2. ollama_chat - Multi-turn conversations

  3. ollama_generate - Single-prompt generation

  4. ollama_pull_model - Download models

  5. ollama_delete_model - Remove models

See API.md for detailed API documentation.

🧪 Testing

Local Testing

# Test stdio transport npm start # Test HTTP transport MCP_TRANSPORT=http npm start # Test health check (HTTP mode) curl http://localhost:8080/healthz

Model Testing

# List available models ollama list # Test a model ollama run llama2 "Hello, how are you?"

📖 Documentation

🤝 Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Add tests if applicable

  5. Submit a pull request

📄 License

MIT License - see LICENSE for details.

🆘 Troubleshooting

Common Issues

"Cannot find module" errors:

npm install npm run build

Ollama connection issues:

# Check if Ollama is running ollama list # Check Ollama service ollama serve

Railway deployment issues:

# Check Railway logs railway logs # Verify environment variables railway variables

Getting Help

Built with ❤️ for the AI community

This server cannot be installed

-
security - not tested
-
license - not tested
-
quality - not tested

How are these scores calculated?

local-only server

The server can only run on the client's local machine because it depends on local resources.

Enables interaction with locally running Ollama models through chat, generation, and model management operations. Supports listing, downloading, and deleting models while maintaining conversation history for interactive sessions.

  1. 🚀 Features
    1. 📋 Prerequisites
      1. 🛠️ Installation
        1. Local Development
        2. Using with Cursor
      2. 🏗️ Architecture
        1. 🔧 Configuration
          1. Environment Variables
          2. Transport Modes
        2. 🚀 Deployment
          1. Railway Deployment
          2. Docker Deployment
        3. 📚 Available Tools
          1. 🧪 Testing
            1. Local Testing
            2. Model Testing
          2. 📖 Documentation
            1. 🤝 Contributing
              1. 📄 License
                1. 🆘 Troubleshooting
                  1. Common Issues
                  2. Getting Help

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