AgentDeck

Build the agent.Own the runtime.

You write agents and workflows as small Python definitions, and skills as SKILL.md directories. AgentDeck owns everything around them: project discovery, settings and provider wiring, tools and MCP servers, sessions, streaming, typed workflows with human approval. Execution stays in the OpenAI Agents SDK and LangGraph.

A whole agent

# .agentdeck/agents/greeter/agent.py
from agentdeck import Agent
 
greeter = Agent(name="Greeter", instructions="You are a friendly scheduling assistant. Keep replies to one short sentence.")

Nothing registers it — the file’s location is the registration. Run it:

import asyncio
 
from agentdeck import Deck
 
 
async def main() -> None:
    async with Deck.from_project() as deck:
        result = await deck.run("Greeter", "hello")
        print(result.output)
 
 
asyncio.run(main())

What you did not write

• Registration — drop a file into .agentdeck/; discovery does the rest.
• Provider and runner config — layered settings from env, .env, and config.yaml.
• Conversation memory — deck.run(..., session_id=...) keeps a session across turns and surfaces; set AGENTDECK_SESSION to keep it across a process restart too.
• Streaming — deck.stream() and an SSE HTTP surface: same agent, no extra code.
• Workflow machinery — graph compilation, durability, and human interrupts from a typed state class.

What AgentDeck is not

No YAML or JSON agent DSL — definitions are Python. No auth system, no marketplace, no hosted control plane. It does not reimplement the engines it runs on.

Install and run one → · How the pieces fit →