User MCP server¶

class datarobot.models.user_mcp_server_deployment.EnumAPIRepresentationConverter¶

class datarobot.models.user_mcp_server_deployment.PromptInUserMCPServerDeployment¶

A prompt registered in one MCP server deployment. It is used to: - Create one prompt and register it in one MCP server deployment. - List tools registered in one MCP server deployment.

• Variables:
  • id (str) – The identifier of prompt.
  • name (str) – The prompt name.
  • type (str) – The prompt type. It is a camelCase string representation of TypeOfPromptInUserMCPServerDeployment.
  • created_at (str) – Datetime when the prompt is created. It is formatted as RFC3339 UTC, e.g., 2026-02-24T19:12:48.285320Z.
  • user_id (bool) – The identifier of user who created the prompt.
  • user_name (str) – The name of user who created the prompt.
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the prompt is registered.

classmethod create(mcp_server_deployment_id, name, type)¶

Create a new MCP prompt and return it.

• Parameters:
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the prompt is registered.
  • name (str) – The prompt name.
  • type (TypeOfPromptInUserMCPServerDeployment) – The prompt type.
• Returns: The created MCP prompt.
• Return type: PromptInUserMCPServerDeployment

classmethod list(mcp_server_deployment_id, offset=0, limit=10)¶

Get a list of MCP prompts.

• Parameters:
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the prompt is registered.
  • offset (int) – The offset of the query.
  • limit (int) – The limit of returned MCP prompt.
• Returns: A list of MCP prompts.
• Return type: List[PromptInUserMCPServerDeployment]

delete()¶

Delete a MCP prompt.

• Return type: None

classmethod from_data(data)¶

Instantiate an object of this class using a dict.

• Parameters: data (dict) – Correctly snake_cased keys and their values.
• Return type: TypeVar(T, bound= APIObject)

classmethod from_server_data(data, keep_attrs=None)¶

Instantiate an object of this class using the data directly from the server, meaning that the keys may have the wrong camel casing

• Parameters:
  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place
  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None
• Return type: TypeVar(T, bound= APIObject)

class datarobot.models.user_mcp_server_deployment.ResourceInUserMCPServerDeployment¶

A resource registered in one MCP server deployment. It is used to: - Create one resource and register it in one MCP server deployment. - List tools registered in one MCP server deployment.

• Variables:
  • id (str) – The identifier of resource.
  • name (str) – The resource name.
  • type (str) – The resource type. It is a camelCase string representation of TypeOfResourceInUserMCPServerDeployment.
  • uri (str) – The resource URI.
  • created_at (str) – Datetime when the resource is created. It is formatted as RFC3339 UTC, e.g., 2026-02-24T19:12:48.285320Z.
  • user_id (bool) – The identifier of user who created the resource.
  • user_name (str) – The name of user who created the resource.
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the resource is registered.

classmethod create(mcp_server_deployment_id, name, type, uri)¶

Create a new MCP resource and return it.

• Parameters:
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the resource is registered.
  • name (str) – The resource name.
  • type (TypeOfResourceInUserMCPServerDeployment) – The resource type.
  • uri (str) – The resource URI.
• Returns: The created MCP resource.
• Return type: ResourceInUserMCPServerDeployment

classmethod list(mcp_server_deployment_id, offset=0, limit=10)¶

Get a list of MCP resources.

• Parameters:
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the resource is registered.
  • offset (int) – The offset of the query.
  • limit (int) – The limit of returned MCP resource.
• Returns: A list of MCP resources.
• Return type: List[ResourceInUserMCPServerDeployment]

delete()¶

Delete a MCP resource.

• Return type: None

classmethod from_data(data)¶

Instantiate an object of this class using a dict.

• Parameters: data (dict) – Correctly snake_cased keys and their values.
• Return type: TypeVar(T, bound= APIObject)

classmethod from_server_data(data, keep_attrs=None)¶

Instantiate an object of this class using the data directly from the server, meaning that the keys may have the wrong camel casing

• Parameters:
  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place
  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None
• Return type: TypeVar(T, bound= APIObject)

class datarobot.models.user_mcp_server_deployment.ToolInUserMCPServerDeployment¶

A tool registered in one MCP server deployment. It is used to: - Create one tool and register it in one MCP server deployment. - List tools registered in one MCP server deployment.

• Variables:
  • id (str) – The identifier of tool.
  • name (str) – The tool name.
  • type (str) – The tool type. It is a camelCase string representation of TypeOfToolInUserMCPServerDeployment.
  • created_at (str) – Datetime when the tool is created. It is formatted as RFC3339 UTC, e.g., 2026-02-24T19:12:48.285320Z.
  • user_id (bool) – The identifier of user who created the tool.
  • user_name (str) – The name of user who created the tool.
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the tool is registered.

classmethod create(mcp_server_deployment_id, name, type)¶

Create a new MCP tool and return it.

• Parameters:
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the tool is registered.
  • name (str) – The tool name.
  • type (TypeOfToolInUserMCPServerDeployment) – The tool type.
• Returns: The created MCP tool.
• Return type: ToolInUserMCPServerDeployment

classmethod list(mcp_server_deployment_id, offset=0, limit=10)¶

Get a list of MCP tools.

• Parameters:
  • mcp_server_deployment_id (str) – The identifier of MCP server deployment (custom model deployment) under which the tool is registered.
  • offset (int) – The offset of the query.
  • limit (int) – The limit of returned MCP tool.
• Returns: A list of MCP tools.
• Return type: List[ToolInUserMCPServerDeployment]

delete()¶

Delete a MCP tool.

• Return type: None

classmethod from_data(data)¶

Instantiate an object of this class using a dict.

• Parameters: data (dict) – Correctly snake_cased keys and their values.
• Return type: TypeVar(T, bound= APIObject)

classmethod from_server_data(data, keep_attrs=None)¶

Instantiate an object of this class using the data directly from the server, meaning that the keys may have the wrong camel casing

• Parameters:
  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place
  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None
• Return type: TypeVar(T, bound= APIObject)

class datarobot.models.user_mcp_server_deployment.TypeOfPromptInUserMCPServerDeployment¶

Supported types of prompts in one user MCP server deployment

USER_PROMPT_TEMPLATE : A prompt template created as an MCP prompt decorated function within the user MCP server.

USER_PROMPT_TEMPLATE_VERSION : A prompt template created and registered in DataRobot.

class datarobot.models.user_mcp_server_deployment.TypeOfResourceInUserMCPServerDeployment¶

Supported types of resources in one user MCP server deployment

USER_RESOURCE : A resource created as an MCP resource decorated function within the user MCP server.

class datarobot.models.user_mcp_server_deployment.TypeOfToolInUserMCPServerDeployment¶

Supported types of tools in one user MCP server deployment

USER_TOOL : A tool created as an MCP tool decorated Python function within the user MCP server.

BUILT_IN_TOOL : A DataRobot Predictive AI tool or wrapper tool of external service (e.g., GitHub).

USER_TOOL_DEPLOYMENT : A tool created as a custom inference model.

class datarobot.models.user_mcp_server_version.PromptInUserMCPServerVersion¶

A prompt registered in one MCP server version. It is used to: - List prompts registered in one MCP server version.

• Variables:
  • id (str) – The identifier of prompt.
  • name (str) – The prompt name.
  • type (str) – The prompt type. It is a camelized string representation of TypeOfPromptInUserMCPServerVersion.
  • created_at (str) – Datetime when the prompt is created. It is formatted as RFC3339 UTC, e.g. 2026-02-24T19:12:48.285320Z
  • user_id (bool) – The identifier of user who created the prompt.
  • user_name (str) – The name of user who created the prompt.
  • mcp_server_version_id (str) – The identifier of MCP server version (custom model version) under which the prompt is registered.

classmethod list(mcp_server_version_id, offset=0, limit=10)¶

Get a list of MCP prompts.

• Parameters:
  • mcp_server_version_id (str) – The identifier of MCP server version (custom model version) under which the prompt is registered.
  • offset (int) – The offset of the query.
  • limit (int) – The limit of returned MCP prompt.
• Returns: A list of MCP prompts.
• Return type: List[PromptInUserMCPServerVersion]

classmethod from_data(data)¶

Instantiate an object of this class using a dict.

• Parameters: data (dict) – Correctly snake_cased keys and their values.
• Return type: TypeVar(T, bound= APIObject)

classmethod from_server_data(data, keep_attrs=None)¶

Instantiate an object of this class using the data directly from the server, meaning that the keys may have the wrong camel casing

• Parameters:
  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place
  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None
• Return type: TypeVar(T, bound= APIObject)

class datarobot.models.user_mcp_server_version.ResourceInUserMCPServerVersion¶

A resource registered in one MCP server version. It is used to: - List resources registered in one MCP server version.

• Variables:
  • id (str) – The identifier of resource.
  • name (str) – The resource name.
  • type (str) – The resource type. It is a camelized string representation of TypeOfResourceInUserMCPServerVersion.
  • uri (str) – The resource URI.
  • created_at (str) – Datetime when the resource is created. It is formatted as RFC3339 UTC, e.g. 2026-02-24T19:12:48.285320Z
  • user_id (bool) – The identifier of user who created the resource.
  • user_name (str) – The name of user who created the resource.
  • mcp_server_version_id (str) – The identifier of MCP server version (custom model version) under which the resource is registered.

classmethod list(mcp_server_version_id, offset=0, limit=10)¶

Get a list of MCP resources.

• Parameters:
  • mcp_server_version_id (str) – The identifier of MCP server version (custom model version) under which the resource is registered.
  • offset (int) – The offset of the query.
  • limit (int) – The limit of returned MCP resource.
• Returns: A list of MCP resources.
• Return type: List[ResourceInUserMCPServerVersion]

classmethod from_data(data)¶

Instantiate an object of this class using a dict.

• Parameters: data (dict) – Correctly snake_cased keys and their values.
• Return type: TypeVar(T, bound= APIObject)

classmethod from_server_data(data, keep_attrs=None)¶

Instantiate an object of this class using the data directly from the server, meaning that the keys may have the wrong camel casing

• Parameters:
  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place
  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None
• Return type: TypeVar(T, bound= APIObject)

class datarobot.models.user_mcp_server_version.ToolInUserMCPServerVersion¶

A tool registered in one MCP server version. It is used to: - List tools registered in one MCP server version.

• Variables:
  • id (str) – The identifier of tool.
  • name (str) – The tool name.
  • type (str) – The tool type. It is a camelized string representation of TypeOfToolInUserMCPServerVersion
  • created_at (str) – Datetime when the tool is created. It is formatted as RFC3339 UTC, e.g. 2026-02-24T19:12:48.285320Z
  • user_id (bool) – The identifier of user who created the tool.
  • user_name (str) – The name of user who created the tool.
  • mcp_server_version_id (str) – The identifier of MCP server version (custom model version) under which the tool is registered.

classmethod list(mcp_server_version_id, offset=0, limit=10)¶

Get a list of MCP tools.

• Parameters:
  • mcp_server_version_id (str) – The identifier of MCP server version (custom model version) under which the tool is registered.
  • offset (int) – The offset of the query.
  • limit (int) – The limit of returned MCP tool.
• Returns: A list of MCP tools.
• Return type: List[ToolInUserMCPServerVersion]

classmethod from_data(data)¶

Instantiate an object of this class using a dict.

• Parameters: data (dict) – Correctly snake_cased keys and their values.
• Return type: TypeVar(T, bound= APIObject)

classmethod from_server_data(data, keep_attrs=None)¶

Instantiate an object of this class using the data directly from the server, meaning that the keys may have the wrong camel casing

• Parameters:
  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place
  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None
• Return type: TypeVar(T, bound= APIObject)

class datarobot.models.user_mcp_server_version.TypeOfPromptInUserMCPServerVersion¶

Supported types of prompts associated with one user MCP server version

USER_PROMPT_TEMPLATE : A prompt template created as a mcp prompt decorated function within the user MCP server.

class datarobot.models.user_mcp_server_version.TypeOfResourceInUserMCPServerVersion¶

Supported types of resources associated with one user MCP server version

USER_RESOURCE : A resource created as a mcp resource decorated function within the user MCP server.

class datarobot.models.user_mcp_server_version.TypeOfToolInUserMCPServerVersion¶

Supported types of tools associated with one user MCP server version

USER_TOOL : A tool created as a mcp tool decorated python function within the user MCP server.

BUILT_IN_TOOL : A DataRobot Predictive AI tool or wrapper tool of external service (e.g., github).