GPU tools for agent frameworks

Four small Python packages give an agent the Node Lodge GPU tools: list machines, check the balance, launch a session, follow it and stop it. They share one toolkit that holds your cost caps and stops every session the agent launched when your code is done with it.

For agents that speak MCP natively, such as Claude Desktop or Claude Code, use the MCP server instead.

The caps

from nodelodge.agent_tools import GpuToolkit

with GpuToolkit(max_cost_usd_per_session=5, max_total_usd=20) as toolkit:
    ...  # give the toolkit's tools to your agent
# every session the agent launched is stopped here

• max_cost_usd_per_session is required. A launch above it is refused before anything is sent to Node Lodge.
• max_total_usd limits the sum of the budgets of the sessions this toolkit launches.
• Node Lodge enforces the limits of the API key on top: give the agent its own key, with Spending limits, in Keys.
• Leaving the with block, calling toolkit.close(), or the end of the Python process stops every session the toolkit launched.
• A refusal (a cap, your credit, a limit of the key, an invalid input) reaches the model as an error with a reason, so it can stop and tell you instead of retrying with more.

The key comes from NODELODGE_API_KEY, the SSH key from ~/.ssh/id_ed25519.pub, and the address allowed to connect is your public IPv4 address. Each can be passed to GpuToolkit instead.

LangChain

from langchain.agents import create_agent
from nodelodge_langchain import nodelodge_tools

with GpuToolkit(max_cost_usd_per_session=5) as toolkit:
    agent = create_agent("anthropic:claude-sonnet-5-5", tools=nodelodge_tools(toolkit))
    agent.invoke({"messages": [{"role": "user", "content": "Launch the cheapest GPU with 48 GB of VRAM."}]})

LlamaIndex

from llama_index.core.agent.workflow import FunctionAgent
from nodelodge_llamaindex import nodelodge_tools

with GpuToolkit(max_cost_usd_per_session=5) as toolkit:
    agent = FunctionAgent(tools=nodelodge_tools(toolkit), llm=llm)
    await agent.run("Launch the cheapest GPU with 48 GB of VRAM.")

OpenAI Agents SDK

from agents import Agent, Runner
from nodelodge_agents import openai_agents_tools

with GpuToolkit(max_cost_usd_per_session=5) as toolkit:
    agent = Agent(name="gpu-ops", tools=openai_agents_tools(toolkit))
    result = await Runner.run(agent, "Launch the cheapest GPU with 48 GB of VRAM.")

Launching and stopping a session pause the run for your approval (result.interruptions in the SDK). Pass require_approval=False to let the agent act alone, within the caps.

Claude Agent SDK

from claude_agent_sdk import ClaudeAgentOptions, query
from nodelodge_agents import claude_allowed_tools, claude_mcp_server

with GpuToolkit(max_cost_usd_per_session=5) as toolkit:
    options = ClaudeAgentOptions(
        mcp_servers={"nodelodge": claude_mcp_server(toolkit)},
        allowed_tools=claude_allowed_tools(["list_offers", "get_balance", "get_session", "list_sessions"]),
    )
    async for message in query(prompt="Launch the cheapest GPU with 48 GB of VRAM.", options=options):
        print(message)

The tools run in your process as an in-process MCP server. Pre-approving only the read-only tools, as above, keeps launching and stopping behind the SDK’s permission prompt.

Tools