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Paper Search MCP

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download_semantic

Download PDF files from Semantic Scholar using paper IDs, DOIs, arXiv IDs, or URLs to save academic papers for research and reference.

Instructions

Download PDF of a Semantic Scholar paper.

Args: paper_id: Semantic Scholar paper ID, Paper identifier in one of the following formats: - Semantic Scholar ID (e.g., "649def34f8be52c8b66281af98ae884c09aef38b") - DOI: (e.g., "DOI:10.18653/v1/N18-3011") - ARXIV: (e.g., "ARXIV:2106.15928") - MAG: (e.g., "MAG:112218234") - ACL: (e.g., "ACL:W12-3903") - PMID: (e.g., "PMID:19872477") - PMCID: (e.g., "PMCID:2323736") - URL: (e.g., "URL:https://arxiv.org/abs/2106.15928v1") save_path: Directory to save the PDF (default: './downloads'). Returns: Path to the downloaded PDF file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paper_idYes
save_pathNo./downloads

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `download_semantic` function is the handler that implements the downloading logic for Semantic Scholar papers by delegating to `semantic_searcher.download_pdf`.
    async def download_semantic(paper_id: str, save_path: str = "./downloads") -> str:
        """Download PDF of a Semantic Scholar paper.    
    
        Args:
            paper_id: Semantic Scholar paper ID, Paper identifier in one of the following formats:
                - Semantic Scholar ID (e.g., "649def34f8be52c8b66281af98ae884c09aef38b")
                - DOI:<doi> (e.g., "DOI:10.18653/v1/N18-3011")
                - ARXIV:<id> (e.g., "ARXIV:2106.15928")
                - MAG:<id> (e.g., "MAG:112218234")
                - ACL:<id> (e.g., "ACL:W12-3903")
                - PMID:<id> (e.g., "PMID:19872477")
                - PMCID:<id> (e.g., "PMCID:2323736")
                - URL:<url> (e.g., "URL:https://arxiv.org/abs/2106.15928v1")
            save_path: Directory to save the PDF (default: './downloads').
        Returns:
            Path to the downloaded PDF file.
        """ 
        return semantic_searcher.download_pdf(paper_id, save_path)
  • The tool is registered with the MCP server using the `@mcp.tool()` decorator.
    @mcp.tool()
    async def download_semantic(paper_id: str, save_path: str = "./downloads") -> str:
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that the tool downloads a PDF and saves it to a directory, but does not mention potential behavioral traits like network dependencies, error handling (e.g., if paper_id is invalid), file overwriting, or authentication needs. It adds basic context but lacks depth on operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear purpose statement, detailed 'Args' and 'Returns' sections. It is appropriately sized, though the list of paper_id formats is lengthy but necessary. Every sentence adds value, and it is front-loaded with the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (handling multiple ID formats), low schema coverage (0%), and presence of an output schema (which covers return values), the description is complete. It fully explains parameters, purpose, and output, compensating for the lack of annotations and schema details, making it sufficient for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It provides extensive semantics for 'paper_id', listing multiple identifier formats with examples, and explains 'save_path' with its default value. This adds significant meaning beyond the bare schema, fully documenting both parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Download PDF') and resource ('Semantic Scholar paper'), distinguishing it from sibling tools like 'read_semantic_paper' (which likely reads content) and other download tools for different sources (e.g., 'download_arxiv'). It precisely defines the tool's function without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for downloading PDFs from Semantic Scholar, but does not explicitly state when to use this tool versus alternatives like 'download_with_fallback' or 'read_semantic_paper'. It provides clear context (downloading PDFs) but lacks explicit guidance on exclusions or comparisons with sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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