Agent Platform API . projects . locations . agents

Instance Methods

operations()

Returns the operations Resource.

close()

Close httplib2 connections.

create(parent, body=None, x__xgafv=None)

Creates an agent.

delete(name, x__xgafv=None)

Deletes an agent.

get(name, x__xgafv=None)

Retrieves an agent.

list(parent, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)

Lists agents in a location.

list_next()

Retrieves the next page of results.

patch(name, body=None, updateMask=None, x__xgafv=None)

Updates an agent.

Method Details

close()
Close httplib2 connections.
create(parent, body=None, x__xgafv=None)
Creates an agent.

Args:
  parent: string, Required. The resource name of the location to create the agent in. Format: `projects/{project}/locations/{location}`. (required)
  body: object, The request body.
    The object takes the form of:

{ # A Vertex agent contains instructions and configurations for the LLM to execute a certain task.
  "base_agent": "A String", # Required. The base agent for the agent. Supported values: * `antigravity-preview-05-2026`
  "base_environment": "", # Optional. The base environment configuration for the agent. Valid types: * A string value for the environment ID, or `remote` for the default. * A struct value for the `environment_config`.
  "created": "A String", # Output only. The time the agent was created.
  "description": "A String", # Optional. The description of the agent.
  "id": "A String", # Immutable. The user-specified ID for the agent. This ID becomes the final component of the agent resource name. If not provided, Vertex AI will generate a value for this ID. The ID can be up to 63 characters and must match the regular expression `[a-z]([a-z0-9-]{0,61}[a-z0-9])?`.
  "metadata": { # Optional. The metadata for the agent.
    "a_key": "A String",
  },
  "name": "A String", # Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.
  "object": "A String", # Output only. The object type of the resource. For agents, the value is `agent`.
  "system_instruction": "A String", # Optional. The instructions for the agent to follow. These instructions are passed to the LLM as a system instruction.
  "tools": [ # Optional. The tools available to the agent.
    { # A tool provides a list of actions available to the Agent during the process of executing a task.
      "headers": { # Optional. The headers for the MCP server, such as for authentication. Only applicable when `type` is `mcp_server`.
        "a_key": "A String",
      },
      "name": "A String", # Optional. The name of the MCP server. Only applicable when `type` is `mcp_server`.
      "type": "A String", # Required. The type of the tool. Supported types: * `code_execution` * `filesystem` * `google_search` * `mcp_server` * `url_context`
      "url": "A String", # Optional. The URL for the MCP server endpoint. Only applicable when `type` is `mcp_server`.
    },
  ],
  "updated": "A String", # Output only. The time the agent was last updated.
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # This resource represents a long-running operation that is the result of a network API call.
  "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
  "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
    "code": 42, # The status code, which should be an enum value of google.rpc.Code.
    "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        "a_key": "", # Properties of the object. Contains field @type with type URL.
      },
    ],
    "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
    "a_key": "", # Properties of the object. Contains field @type with type URL.
  },
  "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
  "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
    "a_key": "", # Properties of the object. Contains field @type with type URL.
  },
}
delete(name, x__xgafv=None)
Deletes an agent.

Args:
  name: string, Required. The resource name of the agent to delete. Format: `projects/{project}/locations/{location}/agents/{agent}`. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # This resource represents a long-running operation that is the result of a network API call.
  "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
  "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
    "code": 42, # The status code, which should be an enum value of google.rpc.Code.
    "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
      {
        "a_key": "", # Properties of the object. Contains field @type with type URL.
      },
    ],
    "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
  },
  "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
    "a_key": "", # Properties of the object. Contains field @type with type URL.
  },
  "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
  "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
    "a_key": "", # Properties of the object. Contains field @type with type URL.
  },
}
get(name, x__xgafv=None)
Retrieves an agent.

Args:
  name: string, Required. The resource name of the agent to retrieve. Format: `projects/{project}/locations/{location}/agents/{agent}`. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A Vertex agent contains instructions and configurations for the LLM to execute a certain task.
  "base_agent": "A String", # Required. The base agent for the agent. Supported values: * `antigravity-preview-05-2026`
  "base_environment": "", # Optional. The base environment configuration for the agent. Valid types: * A string value for the environment ID, or `remote` for the default. * A struct value for the `environment_config`.
  "created": "A String", # Output only. The time the agent was created.
  "description": "A String", # Optional. The description of the agent.
  "id": "A String", # Immutable. The user-specified ID for the agent. This ID becomes the final component of the agent resource name. If not provided, Vertex AI will generate a value for this ID. The ID can be up to 63 characters and must match the regular expression `[a-z]([a-z0-9-]{0,61}[a-z0-9])?`.
  "metadata": { # Optional. The metadata for the agent.
    "a_key": "A String",
  },
  "name": "A String", # Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.
  "object": "A String", # Output only. The object type of the resource. For agents, the value is `agent`.
  "system_instruction": "A String", # Optional. The instructions for the agent to follow. These instructions are passed to the LLM as a system instruction.
  "tools": [ # Optional. The tools available to the agent.
    { # A tool provides a list of actions available to the Agent during the process of executing a task.
      "headers": { # Optional. The headers for the MCP server, such as for authentication. Only applicable when `type` is `mcp_server`.
        "a_key": "A String",
      },
      "name": "A String", # Optional. The name of the MCP server. Only applicable when `type` is `mcp_server`.
      "type": "A String", # Required. The type of the tool. Supported types: * `code_execution` * `filesystem` * `google_search` * `mcp_server` * `url_context`
      "url": "A String", # Optional. The URL for the MCP server endpoint. Only applicable when `type` is `mcp_server`.
    },
  ],
  "updated": "A String", # Output only. The time the agent was last updated.
}
list(parent, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)
Lists agents in a location.

Args:
  parent: string, Required. The resource name of the location to list agents from. Format: `projects/{project}/locations/{location}`. (required)
  orderBy: string, Optional. A comma-separated list of fields to order by. Supported fields: * `created` * `updated` Use `desc` after a field name for descending order. Example: `created desc`.
  pageSize: integer, Optional. The maximum number of agents to return. The service may return fewer than this value. The maximum page size is 100; values above 100 will be coerced to 100. If unspecified, the default page size is 10.
  pageToken: string, Optional. A page token, received from a previous AgentService.ListAgents call. Provide this to retrieve the subsequent page.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for AgentService.ListAgents.
  "agents": [ # The agents matching the request.
    { # A Vertex agent contains instructions and configurations for the LLM to execute a certain task.
      "base_agent": "A String", # Required. The base agent for the agent. Supported values: * `antigravity-preview-05-2026`
      "base_environment": "", # Optional. The base environment configuration for the agent. Valid types: * A string value for the environment ID, or `remote` for the default. * A struct value for the `environment_config`.
      "created": "A String", # Output only. The time the agent was created.
      "description": "A String", # Optional. The description of the agent.
      "id": "A String", # Immutable. The user-specified ID for the agent. This ID becomes the final component of the agent resource name. If not provided, Vertex AI will generate a value for this ID. The ID can be up to 63 characters and must match the regular expression `[a-z]([a-z0-9-]{0,61}[a-z0-9])?`.
      "metadata": { # Optional. The metadata for the agent.
        "a_key": "A String",
      },
      "name": "A String", # Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.
      "object": "A String", # Output only. The object type of the resource. For agents, the value is `agent`.
      "system_instruction": "A String", # Optional. The instructions for the agent to follow. These instructions are passed to the LLM as a system instruction.
      "tools": [ # Optional. The tools available to the agent.
        { # A tool provides a list of actions available to the Agent during the process of executing a task.
          "headers": { # Optional. The headers for the MCP server, such as for authentication. Only applicable when `type` is `mcp_server`.
            "a_key": "A String",
          },
          "name": "A String", # Optional. The name of the MCP server. Only applicable when `type` is `mcp_server`.
          "type": "A String", # Required. The type of the tool. Supported types: * `code_execution` * `filesystem` * `google_search` * `mcp_server` * `url_context`
          "url": "A String", # Optional. The URL for the MCP server endpoint. Only applicable when `type` is `mcp_server`.
        },
      ],
      "updated": "A String", # Output only. The time the agent was last updated.
    },
  ],
  "nextPageToken": "A String", # A token to retrieve the next page of results. Pass this value as ListAgentsRequest.page_token in a subsequent call.
}
list_next()
Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call 'execute()' on to request the next
          page. Returns None if there are no more items in the collection.
        
patch(name, body=None, updateMask=None, x__xgafv=None)
Updates an agent.

Args:
  name: string, Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`. (required)
  body: object, The request body.
    The object takes the form of:

{ # A Vertex agent contains instructions and configurations for the LLM to execute a certain task.
  "base_agent": "A String", # Required. The base agent for the agent. Supported values: * `antigravity-preview-05-2026`
  "base_environment": "", # Optional. The base environment configuration for the agent. Valid types: * A string value for the environment ID, or `remote` for the default. * A struct value for the `environment_config`.
  "created": "A String", # Output only. The time the agent was created.
  "description": "A String", # Optional. The description of the agent.
  "id": "A String", # Immutable. The user-specified ID for the agent. This ID becomes the final component of the agent resource name. If not provided, Vertex AI will generate a value for this ID. The ID can be up to 63 characters and must match the regular expression `[a-z]([a-z0-9-]{0,61}[a-z0-9])?`.
  "metadata": { # Optional. The metadata for the agent.
    "a_key": "A String",
  },
  "name": "A String", # Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.
  "object": "A String", # Output only. The object type of the resource. For agents, the value is `agent`.
  "system_instruction": "A String", # Optional. The instructions for the agent to follow. These instructions are passed to the LLM as a system instruction.
  "tools": [ # Optional. The tools available to the agent.
    { # A tool provides a list of actions available to the Agent during the process of executing a task.
      "headers": { # Optional. The headers for the MCP server, such as for authentication. Only applicable when `type` is `mcp_server`.
        "a_key": "A String",
      },
      "name": "A String", # Optional. The name of the MCP server. Only applicable when `type` is `mcp_server`.
      "type": "A String", # Required. The type of the tool. Supported types: * `code_execution` * `filesystem` * `google_search` * `mcp_server` * `url_context`
      "url": "A String", # Optional. The URL for the MCP server endpoint. Only applicable when `type` is `mcp_server`.
    },
  ],
  "updated": "A String", # Output only. The time the agent was last updated.
}

  updateMask: string, Optional. The list of fields to update. If not present, all fields are updated.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A Vertex agent contains instructions and configurations for the LLM to execute a certain task.
  "base_agent": "A String", # Required. The base agent for the agent. Supported values: * `antigravity-preview-05-2026`
  "base_environment": "", # Optional. The base environment configuration for the agent. Valid types: * A string value for the environment ID, or `remote` for the default. * A struct value for the `environment_config`.
  "created": "A String", # Output only. The time the agent was created.
  "description": "A String", # Optional. The description of the agent.
  "id": "A String", # Immutable. The user-specified ID for the agent. This ID becomes the final component of the agent resource name. If not provided, Vertex AI will generate a value for this ID. The ID can be up to 63 characters and must match the regular expression `[a-z]([a-z0-9-]{0,61}[a-z0-9])?`.
  "metadata": { # Optional. The metadata for the agent.
    "a_key": "A String",
  },
  "name": "A String", # Identifier. The resource name of the agent. Format: `projects/{project}/locations/{location}/agents/{agent}`.
  "object": "A String", # Output only. The object type of the resource. For agents, the value is `agent`.
  "system_instruction": "A String", # Optional. The instructions for the agent to follow. These instructions are passed to the LLM as a system instruction.
  "tools": [ # Optional. The tools available to the agent.
    { # A tool provides a list of actions available to the Agent during the process of executing a task.
      "headers": { # Optional. The headers for the MCP server, such as for authentication. Only applicable when `type` is `mcp_server`.
        "a_key": "A String",
      },
      "name": "A String", # Optional. The name of the MCP server. Only applicable when `type` is `mcp_server`.
      "type": "A String", # Required. The type of the tool. Supported types: * `code_execution` * `filesystem` * `google_search` * `mcp_server` * `url_context`
      "url": "A String", # Optional. The URL for the MCP server endpoint. Only applicable when `type` is `mcp_server`.
    },
  ],
  "updated": "A String", # Output only. The time the agent was last updated.
}