dlt._workspace._plugins
is_workspace_dir
def is_workspace_dir(run_dir: str) -> bool
Checks if run_dir contains dlt workspace, this is true if a config file is found
plug_mcp_pipeline
@_plugins.hookimpl(specname="plug_mcp")
def plug_mcp_pipeline(features: Set[str]) -> Optional[McpFeatures]
Contribute pipeline-scoped tools: table inspection, SQL queries.
Activated by the "pipeline" feature. Used by both WorkspaceMCP (features= {"workspace", "pipeline"}) and PipelineMCP (features={"pipeline"}).
plug_mcp_workspace
@_plugins.hookimpl(specname="plug_mcp")
def plug_mcp_workspace(features: Set[str]) -> Optional[McpFeatures]
Contribute workspace-level tools: pipeline discovery.
Activated by the "workspace" feature. Used by WorkspaceMCP only (features= {"workspace", "pipeline"}) so users can list available pipelines.
plug_mcp_toolkit
@_plugins.hookimpl(specname="plug_mcp")
def plug_mcp_toolkit(features: Set[str]) -> Optional[McpFeatures]
Contribute toolkit discovery tools: list and inspect available toolkits.
Activated by the "toolkit" feature.
plug_mcp_secrets
@_plugins.hookimpl(specname="plug_mcp")
def plug_mcp_secrets(features: Set[str]) -> Optional[McpFeatures]
Contribute secrets management tools: list, view-redacted, update.
Activated by the "secrets" feature.
plug_mcp_context
@_plugins.hookimpl(specname="plug_mcp")
def plug_mcp_context(features: Set[str]) -> Optional[McpFeatures]
Contribute AI context tools: search dlthub sources.
Activated by the "context" feature.