get_samples_in_study
Retrieve and paginate sample data linked to a specific cancer study, with options to sort and limit results for targeted analysis in cBioPortal.
Instructions
Get a list of samples associated with a specific cancer study with pagination support.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| direction | No | ASC | |
| limit | No | ||
| page_number | No | ||
| page_size | No | ||
| sort_by | No | ||
| study_id | Yes |
Implementation Reference
- Core handler function in SamplesEndpoints that validates inputs and performs the paginated API request to retrieve samples for a specific study.@handle_api_errors("get samples in study") @validate_paginated_params async def get_samples_in_study( self, study_id: str, page_number: int = 0, page_size: int = 50, sort_by: Optional[str] = None, direction: str = "ASC", limit: Optional[int] = None, ) -> Dict: """ Get a list of samples associated with a specific cancer study with pagination support. """ # Input Validation validate_study_id(study_id) return await self.paginated_request( endpoint=f"studies/{study_id}/samples", page_number=page_number, page_size=page_size, sort_by=sort_by, direction=direction, limit=limit, data_key="samples" )
- cbioportal_mcp/server.py:96-131 (registration)Registers the get_samples_in_study method (and others) as MCP tools by adding them to the FastMCP instance.def _register_tools(self): """Register tool methods as MCP tools.""" # List of methods to register as tools (explicitly defined) tool_methods = [ # Pagination utilities "paginate_results", "collect_all_results", # Studies endpoints "get_cancer_studies", "get_cancer_types", "search_studies", "get_study_details", "get_multiple_studies", # Genes endpoints "search_genes", "get_genes", "get_multiple_genes", "get_mutations_in_gene", # Samples endpoints "get_samples_in_study", "get_sample_list_id", # Molecular profiles endpoints "get_molecular_profiles", "get_clinical_data", "get_gene_panels_for_study", "get_gene_panel_details", ] for method_name in tool_methods: if hasattr(self, method_name): method = getattr(self, method_name) self.mcp.add_tool(method) logger.debug(f"Registered tool: {method_name}") else: logger.warning(f"Method {method_name} not found for tool registration")
- cbioportal_mcp/server.py:274-286 (handler)Server-level delegation handler for get_samples_in_study that forwards calls to the SamplesEndpoints instance. This is the method directly registered as the MCP tool.async def get_samples_in_study( self, study_id: str, page_number: int = 0, page_size: int = 50, sort_by: Optional[str] = None, direction: str = "ASC", limit: Optional[int] = None, ) -> Dict: """Get a list of samples associated with a specific cancer study with pagination support.""" return await self.samples.get_samples_in_study( study_id, page_number, page_size, sort_by, direction, limit )
- Helper method in BaseEndpoint used by the handler to perform the actual paginated API request and response formatting.async def paginated_request( self, endpoint: str, page_number: int = 0, page_size: int = 50, sort_by: Optional[str] = None, direction: str = "ASC", limit: Optional[int] = None, data_key: str = "results", additional_params: Optional[Dict[str, Any]] = None ) -> Dict[str, Any]: """ Make a paginated API request with standardized handling. Args: endpoint: API endpoint to call page_number: Page number to retrieve (0-based) page_size: Number of items per page sort_by: Field to sort by direction: Sort direction (ASC or DESC) limit: Maximum number of items to return data_key: Key name for results in response additional_params: Additional parameters to include in the request Returns: Standardized paginated response """ # Build base pagination parameters api_params = self.build_pagination_params( page_number, page_size, sort_by, direction, limit ) # Add any additional parameters if additional_params: api_params.update(additional_params) # Special behavior for limit=0 (fetch all results) if limit == 0: results_from_api = await collect_all_results( self.api_client, endpoint, params=api_params ) results_for_response = results_from_api has_more = False # We fetched everything else: # Fetch just the requested page results_from_api = await self.api_client.make_api_request( endpoint, params=api_params ) # Apply limit if specified results_for_response = self.apply_limit(results_from_api, limit) # Determine if there might be more data available has_more = self.determine_has_more(results_from_api, api_params) return self.build_pagination_response( results_for_response, page_number, page_size, has_more, data_key )