Data: Managed Agents overview

Managed Agents — Overview

Managed Agents provisions a container per session as the agent's workspace. The agent loop runs on Anthropic's orchestration layer; the container is where the agent's tools execute — bash commands, file operations, code. You create a persisted Agent config (model, system prompt, tools, MCP servers, skills), then start Sessions that reference it. The session streams events back to you; you send user messages and tool results in.

⚠️ THE MANDATORY FLOW: Agent (once) → Session (every run)

Why agents are separate objects: versioning. An agent is a persisted, versioned config — every update creates a new immutable version, and sessions pin to a version at creation time. This lets you iterate on the agent (tweak the prompt, add a tool) without breaking sessions already running, roll back if a change regresses, and A/B test versions side-by-side. None of that works if you agents.create() fresh on every run.

Every session references a pre-created /v1/agents object. Create the agent once, store the ID, and reuse it across runs.

If you're about to write sessions.create() with model, system, or tools on the session body — stop. Those fields live on agents.create(). The session takes a pointer only.

When generating code, separate setup from runtime. agents.create() belongs in a setup script (or a guarded if agent_id is None: block), not at the top of the hot path. If the user's code calls agents.create() on every invocation, they're accumulating orphaned agents and paying the create latency for nothing. The correct shape is: create once → persist the ID (config file, env var, secrets manager) → every run loads the ID and calls sessions.create().

To change the agent's behavior, use POST /v1/agents/{id} — don't create a new one. Each update bumps the version; running sessions keep their pinned version, new sessions get the latest (or pin explicitly via {type: "agent", id, version}). See shared/managed-agents-core.md → Agents → Versioning. To change tools/mcp_servers/vault_ids on one running session without touching the agent object, use sessions.update() — see shared/managed-agents-core.md → Updating the agent configuration mid-session.

Beta Headers

Managed Agents is in beta. The SDK sets required beta headers automatically:

Which beta header goes where: The SDK sets managed-agents-2026-04-01 automatically on client.beta.{agents,environments,sessions,vaults,memory_stores}.* calls, and files-api-2025-04-14 / skills-2025-10-02 automatically on client.beta.files.* / client.beta.skills.* calls. You do NOT need to add the Skills or Files beta header when calling Managed Agents endpoints. Exception — session-scoped file listing: client.beta.files.list({scope_id: session.id}) is a Files endpoint that takes a Managed Agents parameter, so it needs both headers. Pass betas: ["managed-agents-2026-04-01"] explicitly on that call (the SDK adds the Files header; you add the Managed Agents one). See shared/managed-agents-environments.md → Session outputs.

Reading Guide

Common Pitfalls

• Agent FIRST, then session — NO EXCEPTIONS — the session's agent field accepts only a string ID or {type: "agent", id, version}. model, system, tools, mcp_servers, skills are top-level fields on POST /v1/agents, never on sessions.create(). If the user hasn't created an agent, that is step zero of every example.
• Agent ONCE, not every run — agents.create() is a setup step. Store the returned agent_id and reuse it; don't call agents.create() at the top of your hot path. If the agent's config needs to change, POST /v1/agents/{id} — each update creates a new version, and sessions can pin to a specific version for reproducibility.
• MCP auth goes through vaults — the agent's mcp_servers array declares {type, name, url} only (no auth). Credentials live in vaults (client.beta.vaults.credentials.create) and attach to sessions via vault_ids. Anthropic auto-refreshes OAuth tokens using the stored refresh token.
• Reconcile resources before the first run — a session with a clear ask but a missing tool, credential, data mount, or context will discover the gap mid-run, then flail and give up. Before creating the session, check that every action in the task maps to a configured tool/MCP server, every MCP server has a vault credential, and every referenced file/host is mounted/reachable. When helping a user set one up, run the reconciliation in shared/managed-agents-onboarding.md → §3 Pre-flight viability check.
• Stream to get events — GET /v1/sessions/{id}/events/stream is the primary way to receive agent output in real-time.
• SSE stream has no replay — reconnect with consolidation — if the stream drops while a agent.tool_use, agent.mcp_tool_use, or agent.custom_tool_use is pending resolution (user.tool_confirmation for the first two, user.custom_tool_result for the last one), the session deadlocks (client disconnects → session idles → reconnect happens → no client resolution happens). On every (re)connect: open stream with GET /v1/sessions/{id}/events/stream , fetch GET /v1/sessions/{id}/events, dedupe by event ID, then proceed. See shared/managed-agents-events.md → Reconnecting after a dropped stream.
• Don't trust HTTP-library timeouts as wall-clock caps — requests timeout=(c, r) and httpx.Timeout(n) are per-chunk read timeouts; they reset every byte, so a trickling connection can block indefinitely. For a hard deadline on raw-HTTP polling, track time.monotonic() at the loop level and bail explicitly. Prefer the SDK's sessions.events.stream() / session.events.list() over hand-rolled HTTP. See shared/managed-agents-events.md → Receiving Events.
• Messages queue — you can send events while the session is running or idle; they're processed in order. No need to wait for a response before sending the next message.
• Environment config.type is "cloud" or "self_hosted" — cloud runs the container on Anthropic's infrastructure; self_hosted moves tool execution to your own (see shared/managed-agents-self-hosted-sandboxes.md).
• Archive is permanent on every resource — archiving an agent, environment, session, vault, credential, or memory store makes it read-only with no unarchive. For agents, environments, and memory stores specifically, archived resources cannot be referenced by new sessions (existing sessions continue). Do not call .archive() on a production agent, environment, or memory store as cleanup — always confirm with the user before archiving.