prime-mcp-server

# Prime MCP Server Model Context Protocol (MCP) server for Prime Intellect - manage GPU pods, check availability, and control compute resources through MCP. ## Features - **GPU Availability Checking** - Search for available GPU instances across providers - **Pod Management** - Create, list, monitor, and delete GPU pods - **Cluster Support** - Check multi-node cluster availability - **SSH Key Management** - Manage SSH keys for pod access ## Demo  ## Installation ```bash pip install prime-mcp-server ``` Or with uv: ```bash uv pip install prime-mcp-server ``` ## Configuration Prime MCP uses `prime-core` for configuration, which supports multiple authentication methods: ### Option 1: Environment Variable ```bash export PRIME_API_KEY="your-api-key" ``` ### Option 2: Prime CLI Login (Recommended) ```bash prime login ``` This stores your API key in `~/.prime/config.json` and is shared across all Prime tools. ### Option 3: Config File Manually edit `~/.prime/config.json`: ```json { "api_key": "your-api-key", "base_url": "https://api.primeintellect.ai" } ``` ## Quick Start ### Running the MCP Server ```bash python -m prime_mcp.mcp ``` The server runs over stdio and can be integrated with MCP clients (like Claude Desktop, IDEs, or other MCP-compatible tools). ## Available Tools For complete documentation of all available tools and their parameters, see [docs.primeintellect.ai](https://docs.primeintellect.ai/api-reference/introduction). ## Development ```bash # Clone the repo git clone https://github.com/PrimeIntellect-ai/prime.git cd prime/packages/prime-mcp-server # Install dependencies uv sync # Run tests uv run pytest # Run linter uv run ruff check . ``` ## Related Packages - **`prime`** - Full CLI + SDK with pods, sandboxes, inference, and more - **`prime-sandboxes`** - SDK for managing remote code execution environments - …