search_openalex
Search academic papers from OpenAlex using a query to find relevant research publications and metadata.
Instructions
Search academic papers from OpenAlex.
Args: query: Search query string (e.g., 'machine learning'). 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 | ||
| max_results | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- paper_search_mcp/server.py:862-873 (handler)The tool 'search_openalex' is defined as an MCP tool using the @mcp.tool() decorator and implemented as an asynchronous function. It wraps a generic 'async_search' call using an 'openalex_searcher'.
@mcp.tool() async def search_openalex(query: str, max_results: int = 10) -> List[Dict]: """Search academic papers from OpenAlex. Args: query: Search query string (e.g., 'machine learning'). max_results: Maximum number of papers to return (default: 10). Returns: List of paper metadata in dictionary format. """ papers = await async_search(openalex_searcher, query, max_results) return papers if papers else []