Managed Deep Agents - Quickstart
This quickstart guides users through scaffolding, configuring, testing, and deploying a Managed Deep Agent (MDA). The process involves using the MDA CLI to initialize a project structure, setting up API keys for model providers (e.g., OpenAI), defining agent instructions (`instructions.mmd`), and integrating tools like web search. Testing is done locally via `MDA dev` in LangSmith Studio before deploying the final version to the production environment.
Key takeaways
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Project Scaffolding
0:25
Use `uv tool install managed deep agents` followed by `MDA innit <project-name>` to scaffold the agent project. This creates necessary files like `agent.py`, `instructions.mmd`, and populates environment variables.
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Agent Configuration
2:05
The agent's behavior is defined in `instructions.mmd`. Model selection (OpenAI, Google, Anthropic) and tool definitions (e.g., web search) are configured within the project files.
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Local Development Cycle
3:20
To test locally, run `uv sync` to install dependencies, followed by `MDA dev`. This spins up a local LangSmith Studio environment for iteration and testing.
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Production Deployment
4:40
Deployment requires a paid Langsmith account. The process syncs context to the Context Hub—a centralized location for instructions and skills that can be edited via UI without redeployment.