Claude Platform Docs

Create Session

$ ant beta:sessions create
POST/v1/sessions

Create Session

Parameters
--agent: string or BetaManagedAgentsAgentParams { id, type, version } or BetaManagedAgentsAgentWithOverridesParams { id, type, mcp_servers, 5 more }

Body param: Agent identifier. Accepts the agent ID string, which pins the latest version for the session, or an agent object with both id and version specified.

--environment-id: string

Body param: ID of the environment defining the container configuration for this session.

minLength1
maxLength128
--budget: optional object{ max_list_cost, type }

Body param: A hard spend ceiling. The session stops issuing new model requests once the tracked list cost reaches max_list_cost.

--initial-event: optional array of BetaManagedAgentsUserMessageEventParams { content, type } or BetaManagedAgentsUserDefineOutcomeEventParams { description, rubric, type, max_iterations }

Body param: Initial events to send to the session at creation, processed in order. Supports user.message and user.define_outcome events. Maximum 50 events.

--metadata: optional map[string]

Body param: Arbitrary key-value metadata attached to the session. Maximum 16 pairs, keys up to 64 chars, values up to 512 chars.

--resource: optional array of BetaManagedAgentsGitHubRepositoryResourceParams { authorization_token, type, url, 2 more } or BetaManagedAgentsFileResourceParams { file_id, type, mount_path } or BetaManagedAgentsMemoryStoreResourceParam { memory_store_id, type, access, instructions }

Body param: Resources (e.g. repositories, files) to mount into the session's container.

--title: optional string

Body param: Human-readable session title.

maxLength500
--vault-id: optional array of string

Body param: Vault IDs for stored credentials the agent can use during the session.

--beta: optional array of AnthropicBeta

Header param: Optional header to specify the beta version(s) you want to use.

Returns
beta_managed_agents_session: object{ id, agent, archived_at, 14 more }

A Managed Agents session.

id: string
agent: object{ id, description, mcp_servers, 8 more }

Resolved agent definition for a session. Snapshot of the agent at session creation time.

id: string
description: string
mcp_servers: array of BetaManagedAgentsMCPServerURLDefinition { name, type, url }
name: string
type: "url"
url: string
model: object{ id, effort, inference_geo, speed }

Model identifier and configuration.

id: "claude-sonnet-5" or "claude-fable-5" or "claude-opus-5" or 10 more or string

The model that will power your agent.

See models for additional details and options.

One of the following:
"claude-sonnet-5"

High-performance model for coding and agents

"claude-fable-5"

Next generation of intelligence for the hardest knowledge work and coding problems

"claude-opus-5"

Powerful intelligence for long-running agents and coding

"claude-opus-4-8"

Powerful intelligence for long-running agents and coding

"claude-opus-4-7"

Powerful intelligence for long-running agents and coding

"claude-opus-4-6"

Powerful intelligence for long-running agents and coding

"claude-sonnet-4-6"

Best combination of speed and intelligence

"claude-haiku-4-5"

Fastest model with near-frontier intelligence

"claude-haiku-4-5-20251001"

Fastest model with near-frontier intelligence

"claude-opus-4-5"

Powerful intelligence for long-running agents and coding

"claude-opus-4-5-20251101"

Powerful intelligence for long-running agents and coding

"claude-sonnet-4-5"

High-performance model for agents and coding

"claude-sonnet-4-5-20250929"

High-performance model for agents and coding

effort: optional BetaManagedAgentsEffortLow { type } or BetaManagedAgentsEffortMedium { type } or BetaManagedAgentsEffortHigh { type } or 2 more

How hard Claude works on each turn. Sets output_config.effort on every Messages call the session makes.

One of the following:
beta_managed_agents_effort_low: object{ type }

Low effort. Favors latency over reasoning depth.

type: "low"
beta_managed_agents_effort_medium: object{ type }

Medium effort. Balances latency and reasoning depth.

type: "medium"
beta_managed_agents_effort_high: object{ type }

High effort. Favors reasoning depth.

type: "high"
beta_managed_agents_effort_xhigh: object{ type }

Extra-high effort. Not all models accept this level.

type: "xhigh"
beta_managed_agents_effort_max: object{ type }

Maximum effort. Favors reasoning depth over latency.

type: "max"
inference_geo: optional string

Geographic region for model inference. When unset, requests fall through to the workspace's default_inference_geo.

speed: optional "standard" or "fast"

Inference speed mode. fast provides significantly faster output token generation at premium pricing. Not all models support fast; invalid combinations are rejected at create time.

One of the following:
"standard"
"fast"
multiagent: object{ agents, type }

Resolved coordinator topology with full agent definitions for each roster member.

agents: array of BetaManagedAgentsSessionThreadAgent { id, description, mcp_servers, 7 more } or BetaManagedAgentsAdvisor { model, type }

Full agent definitions the coordinator may spawn as session threads.

One of the following:
beta_managed_agents_session_thread_agent: object{ id, description, mcp_servers, 7 more }

Resolved agent definition for a single session_thread. Snapshot of the agent at thread creation time. The multiagent roster is not repeated here; read it from Session.agent.

beta_managed_agents_advisor: object{ model, type }

Platform advisor roster entry: a model the session's primary thread may consult mid-turn.

model: string

The advisor model id.

type: "advisor"
type: "coordinator"
name: string
skills: array of BetaManagedAgentsAnthropicSkill { skill_id, type, version } or BetaManagedAgentsCustomSkill { skill_id, type, version }
One of the following:
beta_managed_agents_anthropic_skill: object{ skill_id, type, version }

A resolved Anthropic-managed skill.

skill_id: string
type: "anthropic"
version: string
beta_managed_agents_custom_skill: object{ skill_id, type, version }

A resolved user-created custom skill.

skill_id: string
type: "custom"
version: string
system: string
tools: array of BetaManagedAgentsAgentToolset20260401 { configs, default_config, type } or BetaManagedAgentsMCPToolset { configs, default_config, mcp_server_name, type } or BetaManagedAgentsCustomTool { description, input_schema, name, type }
One of the following:
beta_managed_agents_agent_toolset20260401: object{ configs, default_config, type }
beta_managed_agents_mcp_toolset: object{ configs, default_config, mcp_server_name, type }
beta_managed_agents_custom_tool: object{ description, input_schema, name, type }

A custom tool as returned in API responses.

description: string
input_schema: object{ type, properties, required }

JSON Schema for custom tool input parameters.

type: "object"
properties: optional map[unknown]
required: optional array of string
name: string
type: "custom"
type: "agent"
version: number
formatint32
archived_at: string

A timestamp in RFC 3339 format

formatdate-time
budget: object{ max_list_cost, type }

A hard spend ceiling. The session stops issuing new model requests once the tracked list cost reaches max_list_cost.

max_list_cost: object{ amount, currency }

A monetary amount in a specific currency.

amount: string

Amount in minor units of the currency, as an integer decimal string with no leading zeros: "2500" is $25.00 and "50" is fifty cents. A string rather than a number so no float rounding is ever applied.

currency: "USD"

Uppercase ISO-4217 currency code. USD is the only currency currently supported; the accepted set is closed and grows only when a new currency is priced.

type: "limit"
created_at: string

A timestamp in RFC 3339 format

formatdate-time
environment_id: string
metadata: map[string]
outcome_evaluations: array of BetaManagedAgentsOutcomeEvaluationResource { completed_at, description, explanation, 4 more }

Per-outcome evaluation state. One entry per define_outcome event sent to the session.

completed_at: string

A timestamp in RFC 3339 format

formatdate-time
description: string

What the agent should produce.

explanation: string

Grader's verdict text from the most recent evaluation. For satisfied, explains why criteria are met; for needs_revision (intermediate), what's missing; for failed, why unrecoverable.

iteration: number

0-indexed revision cycle the outcome is currently on.

formatint32
outcome_id: string

Server-generated outc_ ID for this outcome.

result: string

Current evaluation state. pending before the agent begins work; running while producing or revising; evaluating while the grader scores; satisfied/max_iterations_reached/failed/interrupted are terminal.

type: "outcome_evaluation"
resources: array of BetaManagedAgentsSessionResource
One of the following:
beta_managed_agents_github_repository_resource: object{ id, created_at, mount_path, 4 more }
id: string
created_at: string

A timestamp in RFC 3339 format

formatdate-time
mount_path: string
type: "github_repository"
updated_at: string

A timestamp in RFC 3339 format

formatdate-time
url: string
checkout: optional BetaManagedAgentsBranchCheckout { name, type } or BetaManagedAgentsCommitCheckout { sha, type }
One of the following:
beta_managed_agents_branch_checkout: object{ name, type }
name: string

Branch name to check out.

minLength1
maxLength255
type: "branch"
beta_managed_agents_commit_checkout: object{ sha, type }
sha: string

Full commit SHA to check out.

minLength7
maxLength64
type: "commit"
beta_managed_agents_file_resource: object{ id, created_at, file_id, 3 more }
id: string
created_at: string

A timestamp in RFC 3339 format

formatdate-time
file_id: string
mount_path: string
type: "file"
updated_at: string

A timestamp in RFC 3339 format

formatdate-time
beta_managed_agents_memory_store_resource: object{ memory_store_id, type, access, 4 more }

A memory store attached to an agent session.

memory_store_id: string

The memory store ID (memstore_...). Must belong to the caller's organization and workspace.

type: "memory_store"
access: optional "read_write" or "read_only"

Access mode for an attached memory store.

One of the following:
"read_write"
"read_only"
description: optional string

Description of the memory store, snapshotted at attach time. Rendered into the agent's system prompt. Empty string when the store has no description.

instructions: optional string

Per-attachment guidance for the agent on how to use this store. Rendered into the memory section of the system prompt. Max 4096 chars.

maxLength4096
mount_path: optional string

Filesystem path where the store is mounted in the session container, e.g. /mnt/memory/user-preferences. Derived from the store's name. Output-only.

name: optional string

Display name of the memory store, snapshotted at attach time. Later edits to the store's name do not propagate to this resource.

stats: object{ active_seconds, duration_seconds }

Timing statistics for a session.

active_seconds: optional number

Cumulative time in seconds the session spent in running status. Excludes idle time.

formatdouble
duration_seconds: optional number

Elapsed time since session creation in seconds. For terminated sessions, frozen at the final update.

formatdouble
status: "rescheduling" or "running" or "idle" or "terminated"

SessionStatus enum

One of the following:
"rescheduling"
"running"
"idle"
"terminated"
title: string
type: "session"
updated_at: string

A timestamp in RFC 3339 format

formatdate-time
usage: object{ active_seconds, cache_creation, cache_read_input_tokens, 4 more }

Cumulative token usage for a session across all turns.

active_seconds: optional number

Cumulative time in seconds during which the session had at least one thread in running status. Overlapping activity from concurrent threads is counted once, unlike stats.active_seconds, which sums each thread's own active time. This is the duration the session's runtime cost is priced on.

formatdouble
cache_creation: optional object{ ephemeral_1h_input_tokens, ephemeral_5m_input_tokens }

Prompt-cache creation token usage broken down by cache lifetime.

ephemeral_1h_input_tokens: optional number

Tokens used to create 1-hour ephemeral cache entries.

formatint32
ephemeral_5m_input_tokens: optional number

Tokens used to create 5-minute ephemeral cache entries.

formatint32
cache_read_input_tokens: optional number

Total tokens read from prompt cache.

formatint32
input_tokens: optional number

Total input tokens consumed across all turns.

formatint32
list_cost: optional object{ amount, currency }

A monetary amount in a specific currency.

amount: string

Amount in minor units of the currency, as an integer decimal string with no leading zeros: "2500" is $25.00 and "50" is fifty cents. A string rather than a number so no float rounding is ever applied.

currency: "USD"

Uppercase ISO-4217 currency code. USD is the only currency currently supported; the accepted set is closed and grows only when a new currency is priced.

output_tokens: optional number

Total output tokens generated across all turns.

formatint32
server_tool_use: optional object{ web_fetch_requests, web_search_requests }

Cumulative count of server-executed tool invocations, broken down by tool.

web_fetch_requests: optional number

Number of server-executed web fetch requests.

formatint32
web_search_requests: optional number

Number of server-executed web search requests.

formatint32
vault_ids: array of string

Vault IDs attached to the session at creation. Empty when no vaults were supplied.

deployment_id: optional string

Deployment ID when the session was created from a deployment reference. Null otherwise.

Create Session

ant beta:sessions create \
  --api-key my-anthropic-api-key \
  --agent agent_011CZkYpogX7uDKUyvBTophP \
  --environment-id env_011CZkZ9X2dpNyB7HsEFoRfW
{
  "id": "sesn_011CZkZAtmR3yMPDzynEDxu7",
  "agent": {
    "id": "agent_011CZkYpogX7uDKUyvBTophP",
    "description": "A general-purpose starter agent.",
    "mcp_servers": [
      {
        "name": "example-mcp",
        "type": "url",
        "url": "https://example-server.modelcontextprotocol.io/sse"
      }
    ],
    "model": {
      "id": "claude-opus-5",
      "effort": {
        "type": "low"
      },
      "inference_geo": "inference_geo",
      "speed": "standard"
    },
    "multiagent": {
      "agents": [
        {
          "id": "agent_011CZkYqphY8vELVzwCUpqiQ",
          "description": "A focused research subagent.",
          "mcp_servers": [
            {
              "name": "example-mcp",
              "type": "url",
              "url": "https://example-server.modelcontextprotocol.io/sse"
            }
          ],
          "model": {
            "id": "claude-opus-5",
            "effort": {
              "type": "low"
            },
            "inference_geo": "inference_geo",
            "speed": "standard"
          },
          "name": "Researcher",
          "skills": [
            {
              "skill_id": "xlsx",
              "type": "anthropic",
              "version": "1"
            }
          ],
          "system": "You are a research subagent that gathers and summarises sources for the coordinating agent.",
          "tools": [
            {
              "configs": [
                {
                  "enabled": true,
                  "name": "bash",
                  "permission_policy": {
                    "type": "always_allow"
                  },
                  "type": "bash"
                }
              ],
              "default_config": {
                "enabled": true,
                "permission_policy": {
                  "type": "always_ask"
                }
              },
              "type": "agent_toolset_20260401"
            }
          ],
          "type": "agent",
          "version": 1
        }
      ],
      "type": "coordinator"
    },
    "name": "My First Agent",
    "skills": [
      {
        "skill_id": "xlsx",
        "type": "anthropic",
        "version": "1"
      },
      {
        "skill_id": "skill_011CZkZFNu9hAbo3jZPRgTlx",
        "type": "custom",
        "version": "2"
      }
    ],
    "system": "You are a general-purpose agent that can research, write code, run commands, and use connected tools to complete the user's task end to end.",
    "tools": [
      {
        "configs": [
          {
            "enabled": true,
            "name": "bash",
            "permission_policy": {
              "type": "always_allow"
            },
            "type": "bash"
          }
        ],
        "default_config": {
          "enabled": true,
          "permission_policy": {
            "type": "always_ask"
          }
        },
        "type": "agent_toolset_20260401"
      }
    ],
    "type": "agent",
    "version": 1
  },
  "archived_at": null,
  "budget": {
    "max_list_cost": {
      "amount": "2500",
      "currency": "USD"
    },
    "type": "limit"
  },
  "created_at": "2026-03-15T10:00:00Z",
  "environment_id": "env_011CZkZ9X2dpNyB7HsEFoRfW",
  "metadata": {},
  "outcome_evaluations": [
    {
      "completed_at": "2026-03-15T10:02:31Z",
      "description": "Produce a 2-page summary as summary.md",
      "explanation": "All five sections present with inline citations.",
      "iteration": 0,
      "outcome_id": "outc_011CZkZRSw2kEfs6ncTVljxP",
      "result": "satisfied",
      "type": "outcome_evaluation"
    }
  ],
  "resources": [
    {
      "id": "sesrsc_011CZkZBJq5dWxk9fVLNcPht",
      "created_at": "2026-03-15T10:00:00Z",
      "file_id": "file_011CNha8iCJcU1wXNR6q4V8w",
      "mount_path": "/uploads/receipt.pdf",
      "type": "file",
      "updated_at": "2026-03-15T10:00:00Z"
    },
    {
      "id": "sesrsc_011CZkZCKr6eXyl0gWMOdQiu",
      "created_at": "2026-03-15T10:00:00Z",
      "mount_path": "/workspace/example-repo",
      "type": "github_repository",
      "updated_at": "2026-03-15T10:00:00Z",
      "url": "https://github.com/example-org/example-repo",
      "checkout": {
        "name": "main",
        "type": "branch"
      }
    }
  ],
  "stats": {
    "active_seconds": 0,
    "duration_seconds": 0
  },
  "status": "idle",
  "title": "Order #1234 inquiry",
  "type": "session",
  "updated_at": "2026-03-15T10:00:00Z",
  "usage": {
    "active_seconds": 0,
    "cache_creation": {
      "ephemeral_1h_input_tokens": 0,
      "ephemeral_5m_input_tokens": 0
    },
    "cache_read_input_tokens": 0,
    "input_tokens": 0,
    "list_cost": {
      "amount": "2500",
      "currency": "USD"
    },
    "output_tokens": 0,
    "server_tool_use": {
      "web_fetch_requests": 0,
      "web_search_requests": 3
    }
  },
  "vault_ids": [
    "vlt_011CZkZDLs7fYzm1hXNPeRjv"
  ],
  "deployment_id": "deployment_id"
}
Returns Examples
{
  "id": "sesn_011CZkZAtmR3yMPDzynEDxu7",
  "agent": {
    "id": "agent_011CZkYpogX7uDKUyvBTophP",
    "description": "A general-purpose starter agent.",
    "mcp_servers": [
      {
        "name": "example-mcp",
        "type": "url",
        "url": "https://example-server.modelcontextprotocol.io/sse"
      }
    ],
    "model": {
      "id": "claude-opus-5",
      "effort": {
        "type": "low"
      },
      "inference_geo": "inference_geo",
      "speed": "standard"
    },
    "multiagent": {
      "agents": [
        {
          "id": "agent_011CZkYqphY8vELVzwCUpqiQ",
          "description": "A focused research subagent.",
          "mcp_servers": [
            {
              "name": "example-mcp",
              "type": "url",
              "url": "https://example-server.modelcontextprotocol.io/sse"
            }
          ],
          "model": {
            "id": "claude-opus-5",
            "effort": {
              "type": "low"
            },
            "inference_geo": "inference_geo",
            "speed": "standard"
          },
          "name": "Researcher",
          "skills": [
            {
              "skill_id": "xlsx",
              "type": "anthropic",
              "version": "1"
            }
          ],
          "system": "You are a research subagent that gathers and summarises sources for the coordinating agent.",
          "tools": [
            {
              "configs": [
                {
                  "enabled": true,
                  "name": "bash",
                  "permission_policy": {
                    "type": "always_allow"
                  },
                  "type": "bash"
                }
              ],
              "default_config": {
                "enabled": true,
                "permission_policy": {
                  "type": "always_ask"
                }
              },
              "type": "agent_toolset_20260401"
            }
          ],
          "type": "agent",
          "version": 1
        }
      ],
      "type": "coordinator"
    },
    "name": "My First Agent",
    "skills": [
      {
        "skill_id": "xlsx",
        "type": "anthropic",
        "version": "1"
      },
      {
        "skill_id": "skill_011CZkZFNu9hAbo3jZPRgTlx",
        "type": "custom",
        "version": "2"
      }
    ],
    "system": "You are a general-purpose agent that can research, write code, run commands, and use connected tools to complete the user's task end to end.",
    "tools": [
      {
        "configs": [
          {
            "enabled": true,
            "name": "bash",
            "permission_policy": {
              "type": "always_allow"
            },
            "type": "bash"
          }
        ],
        "default_config": {
          "enabled": true,
          "permission_policy": {
            "type": "always_ask"
          }
        },
        "type": "agent_toolset_20260401"
      }
    ],
    "type": "agent",
    "version": 1
  },
  "archived_at": null,
  "budget": {
    "max_list_cost": {
      "amount": "2500",
      "currency": "USD"
    },
    "type": "limit"
  },
  "created_at": "2026-03-15T10:00:00Z",
  "environment_id": "env_011CZkZ9X2dpNyB7HsEFoRfW",
  "metadata": {},
  "outcome_evaluations": [
    {
      "completed_at": "2026-03-15T10:02:31Z",
      "description": "Produce a 2-page summary as summary.md",
      "explanation": "All five sections present with inline citations.",
      "iteration": 0,
      "outcome_id": "outc_011CZkZRSw2kEfs6ncTVljxP",
      "result": "satisfied",
      "type": "outcome_evaluation"
    }
  ],
  "resources": [
    {
      "id": "sesrsc_011CZkZBJq5dWxk9fVLNcPht",
      "created_at": "2026-03-15T10:00:00Z",
      "file_id": "file_011CNha8iCJcU1wXNR6q4V8w",
      "mount_path": "/uploads/receipt.pdf",
      "type": "file",
      "updated_at": "2026-03-15T10:00:00Z"
    },
    {
      "id": "sesrsc_011CZkZCKr6eXyl0gWMOdQiu",
      "created_at": "2026-03-15T10:00:00Z",
      "mount_path": "/workspace/example-repo",
      "type": "github_repository",
      "updated_at": "2026-03-15T10:00:00Z",
      "url": "https://github.com/example-org/example-repo",
      "checkout": {
        "name": "main",
        "type": "branch"
      }
    }
  ],
  "stats": {
    "active_seconds": 0,
    "duration_seconds": 0
  },
  "status": "idle",
  "title": "Order #1234 inquiry",
  "type": "session",
  "updated_at": "2026-03-15T10:00:00Z",
  "usage": {
    "active_seconds": 0,
    "cache_creation": {
      "ephemeral_1h_input_tokens": 0,
      "ephemeral_5m_input_tokens": 0
    },
    "cache_read_input_tokens": 0,
    "input_tokens": 0,
    "list_cost": {
      "amount": "2500",
      "currency": "USD"
    },
    "output_tokens": 0,
    "server_tool_use": {
      "web_fetch_requests": 0,
      "web_search_requests": 3
    }
  },
  "vault_ids": [
    "vlt_011CZkZDLs7fYzm1hXNPeRjv"
  ],
  "deployment_id": "deployment_id"
}