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Paper Search MCP

by openags

search_ssrn

Search SSRN academic paper metadata using keywords to find research records. This tool retrieves paper information without downloading PDFs.

Instructions

Search metadata records from SSRN.

Note: SSRN connector is metadata-only and does not support direct PDF download.

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
NameRequiredDescriptionDefault
queryYes
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'search_ssrn' handler which delegates the search query to the SSRNSearcher instance.
    async def search_ssrn(query: str, max_results: int = 10) -> List[Dict]:
        """Search metadata records from SSRN.
    
        Note: SSRN connector is metadata-only and does not support direct PDF download.
    
        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(ssrn_searcher, query, max_results)
        return papers if papers else []
  • The implementation of the search method within the SSRNSearcher class that performs the actual web request and parsing.
    def search(self, query: str, max_results: int = 10, **kwargs) -> List[Paper]:
        """Search SSRN and return metadata records.
    
        Args:
            query: Search terms.
            max_results: Maximum results to return (practical limit ~30 without
                         pagination; SSRN returns ~15 results per page).
            **kwargs: Unused; reserved for future filter support.
    
        Returns:
            List of :class:`~paper_search_mcp.paper.Paper` objects.
        """
        papers: List[Paper] = []
        page = 1
        per_page = 15  # SSRN default
    
        while len(papers) < max_results:
            self._throttle()
            html, err = self._fetch_page(query, page)
            if err or not html:
                logger.warning("SSRN search page %d fetch failed: %s", page, err)
                break
    
            page_papers = self._parse_results(html)
            if not page_papers:
                break
    
            papers.extend(page_papers)
            if len(page_papers) < per_page:
                break  # last page
    
            page += 1
    
        return papers[:max_results]
  • The registration of the search_ssrn tool in the main server task map.
    task_map[source] = search_ssrn(query, max_results_per_source)
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 important behavioral traits: that it's metadata-only and doesn't support PDF downloads. However, it doesn't mention rate limits, authentication needs, pagination behavior, or error handling. The description adds value but doesn't fully compensate for the lack of annotations.

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

Conciseness5/5

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

The description is well-structured and appropriately sized. It starts with the core purpose, adds a critical note, then clearly documents parameters and return values. Every sentence earns its place with no wasted words, and information is front-loaded effectively.

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

Completeness4/5

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

Given the tool's moderate complexity, no annotations, but with an output schema (implied by 'Returns' section), the description is reasonably complete. It covers purpose, limitations, parameters, and return format. The main gap is lack of behavioral details like rate limits or error handling, but the output schema reduces the need to fully describe return values.

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

Parameters4/5

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

With 0% schema description coverage, the description must compensate. It provides clear semantics for both parameters: 'query' is explained as a search query string with an example, and 'max_results' is explained with its default value. This adds meaningful context beyond the bare schema, though it doesn't cover all potential edge cases.

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 tool's purpose with specific verb ('Search') and resource ('metadata records from SSRN'), and distinguishes it from siblings by noting it's metadata-only and doesn't support direct PDF download. This differentiation is explicit and helpful for selection.

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 provides clear context about when to use this tool by stating it's 'metadata-only' and doesn't support direct PDF download, which implicitly suggests alternatives for PDF access. However, it doesn't explicitly name alternative tools or provide explicit 'when-not-to-use' guidance beyond the PDF limitation.

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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