Prerequisites
- A Thunder Compute account
- An AI agent that supports remote MCP servers (Claude Code, Cursor, Codex, etc.)
Setup
- Claude Code
- Codex
- Cursor
- Windsurf
- OpenCode
- Smithery
- Direct HTTP
Run this in your terminal:Then start Claude Code and run
/mcp to authenticate. A browser window will open for you to log in and authorize access.Manual setup
Manual setup
Alternatively, add to
~/.claude.json (global) or .claude.json in your project root:Authentication
No API tokens or environment variables needed. When you first connect, a browser window opens for you to log in with your Thunder Compute account and authorize access. Tokens refresh automatically, so you only authenticate once per session.Available Tools
Instance Management
| Tool | Description |
|---|---|
list_instances | List all GPU instances with status, IP, and configuration |
create_instance | Create a new GPU instance (specify GPU type, template, mode, etc.) |
delete_instance | Delete an instance (irreversible) |
modify_instance | Change instance config (GPU type, vCPUs, disk, mode) |
run_command | Execute a shell command on a running instance and return stdout, stderr, and exit code |
Information
| Tool | Description |
|---|---|
get_specs | Get available GPU specs (VRAM, vCPU options, storage ranges) |
get_availability | Get current GPU availability status for each spec |
get_pricing | Get current per-hour GPU pricing |
list_templates | List available OS templates (Ubuntu, PyTorch, etc.) |
Snapshots
| Tool | Description |
|---|---|
list_snapshots | List all instance snapshots |
create_snapshot | Create a snapshot of an instance |
delete_snapshot | Delete a snapshot (irreversible) |
SSH Keys
| Tool | Description |
|---|---|
list_ssh_keys | List SSH keys in your organization |
create_ssh_key | Add an SSH public key to your organization |
delete_ssh_key | Delete an SSH key |
add_ssh_key_to_instance | Add an SSH public key to a running instance’s authorized_keys |
Port Forwarding
| Tool | Description |
|---|---|
list_ports | List all instances with their forwarded ports |
forward_port | Forward HTTP ports on an instance |
delete_port | Remove forwarded ports from an instance |
Connectivity
| Tool | Description |
|---|---|
get_ssh_command | Get the SSH command to connect to an instance |
get_scp_command | Get the SCP command to copy files to/from an instance |
Billing & Usage
| Tool | Description |
|---|---|
get_meter_data | Get GPU usage metrics for a time period (hourly, daily, weekly, or monthly) |
get_upcoming_invoice | Get estimated charges for the current billing period |
get_invoice_history | Get historical invoices for your organization |
get_subscription | Get subscription details including plan, status, and payment info |
API Tokens
| Tool | Description |
|---|---|
list_tokens | List all named API tokens for your organization |
create_token | Create a new named API token |
delete_token | Delete a named API token |
Prompts
The MCP server includes built-in prompts that guide your agent through common multi-step workflows:| Prompt | Description |
|---|---|
create-dev-instance | Set up a GPU development instance with sensible defaults |
deploy-model | Deploy an ML model (supports Ollama, vLLM, and Transformers) |
check-costs | Review current GPU usage and costs |
snapshot-and-teardown | Save instance state and clean up |
setup-comfyui | Spin up a GPU instance with ComfyUI for AI image generation |
setup-jupyter | Launch a Jupyter Lab environment on a GPU instance |
fine-tune-model | Set up a GPU instance for fine-tuning with LoRA or full fine-tuning |
benchmark-gpu | Run a quick GPU benchmark on an instance to verify performance |
Example Usage
Once configured, you can ask your AI agent things like:- “Spin up an A100 instance with PyTorch”
- “What GPU types are available and how much do they cost?”
- “Which GPUs are available right now?”
- “List my running instances”
- “Run
nvidia-smion my instance” - “Delete instance inst-abc123”
- “Forward port 8080 on my instance”
- “Create a snapshot of my instance before I make changes”
- “Deploy Llama 3 on a GPU”
- “How much have I spent this month?”
- “Show my invoice history”
- “Create an API token for my CI pipeline”
Troubleshooting
Authentication fails or browser doesn’t open: Run/mcp in Claude Code to manually trigger authentication. Make sure you’re logged in to your Thunder Compute account in the browser.
Browser callback fails after clicking Allow (common when running your AI agent inside a remote VM, container, or SSH session): if the browser shows a “can’t connect” / “site can’t be reached” page after consent, copy the full URL from the browser’s address bar (it looks like http://localhost:<port>/callback?code=...&state=...) and paste it into your AI agent where it prompts you to finish authentication. The agent will extract the code from the URL and complete the token exchange itself.
“Protected resource does not match” error: The URL in your MCP config must match the server’s configured resource URL exactly. Ensure you’re using https://www.thundercompute.com/mcp.
“token has invalid issuer” error: This is a server-side configuration issue. The MCP authentication client must be configured with the correct Stytch Connected Apps domain.
Tools not appearing: Restart your AI agent after changing MCP configuration. Most agents only read MCP config on startup.
MCP Directories
Thunder Compute is listed on major MCP directories for easy discovery:- Smithery — One-click install for supported clients
- MCP Registry — The official Model Context Protocol server registry
- Glama — Auto-indexed from the MCP Registry
- PulseMCP — Auto-indexed from the MCP Registry