BioContextAI Knowledgebase MCP

Instructions

Implementation Reference

• src/biocontext_kb/core/pride/_search_pride_projects.py:9-140 (handler)

  Handler function for the 'search_pride_projects' tool (likely referred to as 'bc_search_pride_projects' in some contexts). Implements API call to PRIDE search endpoint, parameter validation, result processing, and error handling. Tool schema defined via Annotated parameters with Pydantic Field descriptions.
  @core_mcp.tool() def search_pride_projects( keyword: Annotated[ Optional[str], Field(description="Search keywords (e.g., 'proteome', 'cancer', 'human')"), ] = None, organism_filter: Annotated[ Optional[str], Field(description="Organism filter (e.g., 'Homo sapiens', 'human')"), ] = None, instrument_filter: Annotated[ Optional[str], Field(description="Instrument type filter (e.g., 'Orbitrap', 'LTQ')"), ] = None, experiment_type_filter: Annotated[ Optional[str], Field(description="Experiment type filter (e.g., 'TMT', 'Label-free')"), ] = None, page_size: Annotated[ int, Field(description="Number of results to return (max 100)"), ] = 20, sort_field: Annotated[ str, Field(description="Sort field: submissionDate or publicationDate"), ] = "submissionDate", sort_direction: Annotated[ str, Field(description="Sort direction: ASC or DESC"), ] = "DESC", ) -> dict: """Search PRIDE database for mass spectrometry proteomics projects using keywords and filters. Returns: dict: Results array with project accessions, titles, descriptions, organisms, instruments, experiment types, count, search_criteria or error message. """ base_url = "https://www.ebi.ac.uk/pride/ws/archive/v3/search/projects" # Build query parameters params: dict[str, str | int] = {} if page_size > 100: page_size = 100 params["pageSize"] = page_size params["page"] = 0 # Add keyword search if keyword: params["keyword"] = keyword # Build filter string for specific criteria filters = [] if organism_filter: filters.append(f"organisms=={organism_filter}") if instrument_filter: filters.append(f"instruments=={instrument_filter}") if experiment_type_filter: filters.append(f"experimentTypes=={experiment_type_filter}") if filters: params["filter"] = ",".join(filters) # Validate and set sort parameters - use only known working fields valid_sort_fields = ["submissionDate", "publicationDate"] if sort_field not in valid_sort_fields: sort_field = "submissionDate" params["sortFields"] = sort_field valid_sort_directions = ["ASC", "DESC"] if sort_direction.upper() not in valid_sort_directions: sort_direction = "DESC" params["sortDirection"] = sort_direction.upper() try: response = requests.get(base_url, params=params) response.raise_for_status() search_results = response.json() if not search_results: return { "results": [], "count": 0, "message": "No PRIDE projects found matching the search criteria", "search_criteria": { "keyword": keyword, "organism_filter": organism_filter, "instrument_filter": instrument_filter, "experiment_type_filter": experiment_type_filter, "sort_field": sort_field, "sort_direction": sort_direction, }, } # Process results to include key information processed_results = [] for project in search_results: processed_project = { "accession": project.get("accession"), "title": project.get("title"), "description": project.get("projectDescription", "")[:500] + "..." if len(project.get("projectDescription", "")) > 500 else project.get("projectDescription", ""), "submission_date": project.get("submissionDate"), "publication_date": project.get("publicationDate"), "organisms": project.get("organisms", []), "instruments": project.get("instruments", []), "experiment_types": project.get("experimentTypes", []), "keywords": project.get("keywords", []), "submitters": project.get("submitters", []), "download_count": project.get("downloadCount", 0), } processed_results.append(processed_project) return { "results": processed_results, "count": len(processed_results), "search_criteria": { "keyword": keyword, "organism_filter": organism_filter, "instrument_filter": instrument_filter, "experiment_type_filter": experiment_type_filter, "sort_field": sort_field, "sort_direction": sort_direction, }, } except requests.exceptions.HTTPError as e: return {"error": f"HTTP error: {e}"} except Exception as e: return {"error": f"Exception occurred: {e!s}"}
• src/biocontext_kb/core/pride/__init__.py:2-2 (registration)

  Imports the search_pride_projects function, allowing it to be discovered and the decorator to register it when the pride module is imported by the MCP server.
  from ._search_pride_projects import search_pride_projects
• src/biocontext_kb/core/pride/_search_pride_projects.py:10-39 (schema)

  Input schema defined using Annotated types and Pydantic Field for descriptions, used by FastMCP for tool input validation.
  def search_pride_projects( keyword: Annotated[ Optional[str], Field(description="Search keywords (e.g., 'proteome', 'cancer', 'human')"), ] = None, organism_filter: Annotated[ Optional[str], Field(description="Organism filter (e.g., 'Homo sapiens', 'human')"), ] = None, instrument_filter: Annotated[ Optional[str], Field(description="Instrument type filter (e.g., 'Orbitrap', 'LTQ')"), ] = None, experiment_type_filter: Annotated[ Optional[str], Field(description="Experiment type filter (e.g., 'TMT', 'Label-free')"), ] = None, page_size: Annotated[ int, Field(description="Number of results to return (max 100)"), ] = 20, sort_field: Annotated[ str, Field(description="Sort field: submissionDate or publicationDate"), ] = "submissionDate", sort_direction: Annotated[ str, Field(description="Sort direction: ASC or DESC"), ] = "DESC", ) -> dict: