search_semantic
Search academic papers from Semantic Scholar using queries with optional year filters to find relevant research publications.
Instructions
Search academic papers from Semantic Scholar.
Args: query: Search query string (e.g., 'machine learning'). year: Optional year filter (e.g., '2019', '2016-2020', '2010-', '-2015'). max_results: Maximum number of papers to return (default: 10). Returns: List of paper metadata in dictionary format.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| year | No | ||
| max_results | No |
Implementation Reference
- paper_search_mcp/server.py:602-616 (handler)The `search_semantic` function is an async handler that performs academic paper searches from Semantic Scholar, accepting a query, optional year, and max_results. It is registered as an MCP tool.
async def search_semantic(query: str, year: Optional[str] = None, max_results: int = 10) -> List[Dict]: """Search academic papers from Semantic Scholar. Args: query: Search query string (e.g., 'machine learning'). year: Optional year filter (e.g., '2019', '2016-2020', '2010-', '-2015'). max_results: Maximum number of papers to return (default: 10). Returns: List of paper metadata in dictionary format. """ kwargs = {} if year is not None: kwargs['year'] = year papers = await async_search(semantic_searcher, query, max_results, **kwargs) return papers if papers else [] - paper_search_mcp/server.py:601-601 (registration)The `search_semantic` tool is registered using the @mcp.tool() decorator.
@mcp.tool()