get_multiple_genes
Retrieve detailed information on multiple genes simultaneously, including gene IDs and types, for cancer genomics research using cBioPortal data integration.
Instructions
Get information about multiple genes concurrently.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| gene_id_type | No | ENTREZ_GENE_ID | |
| gene_ids | Yes | ||
| projection | No | SUMMARY |
Implementation Reference
- Primary handler implementation: batches gene_ids, performs concurrent API calls to /genes/fetch, aggregates results into a dictionary keyed by gene ID with metadata including execution time, batch count, and error count.async def get_multiple_genes( self, gene_ids: List[str], gene_id_type: str = "ENTREZ_GENE_ID", projection: str = "SUMMARY", ) -> Dict: """ Get information about multiple genes concurrently. This method uses concurrency to fetch multiple genes in parallel, which is much more efficient than sequential requests for large batches. Args: gene_ids: List of gene IDs (Entrez IDs or Hugo symbols) gene_id_type: Type of gene ID provided (ENTREZ_GENE_ID or HUGO_GENE_SYMBOL) projection: Level of detail to return (ID, SUMMARY, DETAILED) Returns: Dictionary with gene information and performance metadata """ overall_start_time = time.time() # Single start time for the whole operation if not gene_ids: return { "genes": {}, "metadata": { "count": 0, "total_requested": 0, "errors": 0, "concurrent": True, "batches": 0, "execution_time": round(time.time() - overall_start_time, 3), }, } # For large gene lists, break into smaller batches for API compatibility batch_size = ( self.config.get("api.batch_size.genes", 100) if self.config else 100 # Default to 100 if no config provided ) gene_batches = [ gene_ids[i : i + batch_size] for i in range(0, len(gene_ids), batch_size) ] async def fetch_gene_batch(batch): try: params = {"geneIdType": gene_id_type, "projection": projection} batch_data = await self.api_client.make_api_request( "genes/fetch", method="POST", params=params, json_data=batch ) return {"data": batch_data, "success": True} except Exception as e: return {"error": str(e), "success": False} # Create tasks for all batches and run them concurrently tasks = [fetch_gene_batch(batch) for batch in gene_batches] batch_results = await asyncio.gather(*tasks) # Process results all_genes = [] error_count = 0 for result in batch_results: if result["success"]: all_genes.extend(result["data"]) else: error_count += 1 # Convert to dictionary for easier lookup genes_dict = {} key_field = ( "hugoGeneSymbol" if gene_id_type == "HUGO_GENE_SYMBOL" else "entrezGeneId" ) for gene in all_genes: gene_key_value = gene.get(key_field) if gene_key_value: genes_dict[str(gene_key_value)] = gene return { "genes": genes_dict, "metadata": { "count": len(genes_dict), "total_requested": len(gene_ids), "errors": error_count, "execution_time": round(time.time() - overall_start_time, 3), "concurrent": True, "batches": len(gene_batches), }, }
- cbioportal_mcp/server.py:240-247 (handler)Delegating handler in the main server class that forwards the call to the GenesEndpoints instance.async def get_multiple_genes( self, gene_ids: List[str], gene_id_type: str = "ENTREZ_GENE_ID", projection: str = "SUMMARY", ) -> Dict: """Get information about multiple genes concurrently.""" return await self.genes.get_multiple_genes(gene_ids, gene_id_type, projection)
- cbioportal_mcp/server.py:96-131 (registration)Tool registration block where 'get_multiple_genes' is included in the tool_methods list and registered via FastMCP's add_tool method.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:48-48 (helper)Instantiation of GenesEndpoints instance (self.genes) which contains the primary handler, injected with API client and config.self.genes = GenesEndpoints(self.api_client, config)