Claude Platform Docs

List Agents

$ ant beta:agents list
GET/v1/agents

List Agents

Parameters
--created-at-gte: optional string

Query param: Return agents created at or after this time (inclusive).

formatdate-time
--created-at-lte: optional string

Query param: Return agents created at or before this time (inclusive).

formatdate-time
--include-archived: optional boolean

Query param: Include archived agents in results. Defaults to false.

--limit: optional number

Query param: Maximum results per page. Default 20, maximum 100.

formatint32
--page: optional string

Query param: Opaque pagination cursor from a previous response.

--beta: optional array of AnthropicBeta

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

Returns
BetaManagedAgentsListAgents: object{ data, next_page }

Paginated list of agents.

data: array of BetaManagedAgentsAgent { id, archived_at, created_at, 12 more }

List of agents.

id: string
archived_at: string

A timestamp in RFC 3339 format

formatdate-time
created_at: string

A timestamp in RFC 3339 format

formatdate-time
description: string
mcp_servers: array of BetaManagedAgentsMCPServerURLDefinition { name, type, url }
name: string
type: "url"
url: string
metadata: map[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 a concrete agent roster.

agents: array of BetaManagedAgentsAgentReference { id, type, version } or BetaManagedAgentsAdvisor { model, type }

Agents the coordinator may spawn as session threads, each resolved to a specific version.

One of the following:
beta_managed_agents_agent_reference: object{ id, type, version }

A resolved agent reference with a concrete version.

id: string
type: "agent"
version: number
formatint32
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"
updated_at: string

A timestamp in RFC 3339 format

formatdate-time
version: number

The agent's current version. Starts at 1 and increments when the agent is modified.

formatint32
next_page: optional string

Opaque cursor for the next page. Null when no more results.

List Agents

ant beta:agents list \
  --api-key my-anthropic-api-key
{
  "data": [
    {
      "id": "agent_011CZkYpogX7uDKUyvBTophP",
      "archived_at": null,
      "created_at": "2026-03-15T10:00:00Z",
      "description": "A general-purpose starter agent.",
      "mcp_servers": [
        {
          "name": "example-mcp",
          "type": "url",
          "url": "https://example-server.modelcontextprotocol.io/sse"
        }
      ],
      "metadata": {
        "foo": "bar"
      },
      "model": {
        "id": "claude-opus-5",
        "effort": {
          "type": "low"
        },
        "inference_geo": "inference_geo",
        "speed": "standard"
      },
      "multiagent": {
        "agents": [
          {
            "id": "agent_011CZkYqphY8vELVzwCUpqiQ",
            "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",
      "updated_at": "2026-03-15T10:00:00Z",
      "version": 1
    }
  ],
  "next_page": "next_page"
}
Returns Examples
{
  "data": [
    {
      "id": "agent_011CZkYpogX7uDKUyvBTophP",
      "archived_at": null,
      "created_at": "2026-03-15T10:00:00Z",
      "description": "A general-purpose starter agent.",
      "mcp_servers": [
        {
          "name": "example-mcp",
          "type": "url",
          "url": "https://example-server.modelcontextprotocol.io/sse"
        }
      ],
      "metadata": {
        "foo": "bar"
      },
      "model": {
        "id": "claude-opus-5",
        "effort": {
          "type": "low"
        },
        "inference_geo": "inference_geo",
        "speed": "standard"
      },
      "multiagent": {
        "agents": [
          {
            "id": "agent_011CZkYqphY8vELVzwCUpqiQ",
            "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",
      "updated_at": "2026-03-15T10:00:00Z",
      "version": 1
    }
  ],
  "next_page": "next_page"
}