Paper Search MCP Server

Instructions

USE THIS TOOL WHEN:
- You need broad academic search across ALL disciplines
- You want citation counts and "cited by" information
- Other specialized tools don't cover your topic

COVERAGE: All academic disciplines, books, theses, patents.

LIMITATIONS:
- Uses web scraping (may be rate-limited)
- Does NOT support PDF download

FOR FULL TEXT (try in order):
1. download_arxiv(id) - if arXiv preprint
2. download_scihub(doi) - if published before 2023
3. download_semantic(id) - last resort

Args:
    query: Search terms (any academic topic).
    max_results: Number of results (default: 10, keep small to avoid blocks).

Returns:
    List of paper dicts with: title, authors, abstract snippet,
    citations count, url, source.

Example:
    search_google_scholar("climate change economic impact", max_results=5)

Implementation Reference

• paper_find_mcp/server.py:432-464 (handler)

  MCP tool handler for search_google_scholar. Decorated with @mcp.tool() for registration. Delegates to generic _search using GoogleScholarSearcher.

  @mcp.tool()
  async def search_google_scholar(query: str, max_results: int = 10) -> List[Dict]:
      """Search academic papers on Google Scholar (broad coverage).
      
      USE THIS TOOL WHEN:
      - You need broad academic search across ALL disciplines
      - You want citation counts and "cited by" information
      - Other specialized tools don't cover your topic
      
      COVERAGE: All academic disciplines, books, theses, patents.
      
      LIMITATIONS:
      - Uses web scraping (may be rate-limited)
      - Does NOT support PDF download
      
      FOR FULL TEXT (try in order):
      1. download_arxiv(id) - if arXiv preprint
      2. download_scihub(doi) - if published before 2023
      3. download_semantic(id) - last resort
      
      Args:
          query: Search terms (any academic topic).
          max_results: Number of results (default: 10, keep small to avoid blocks).
      
      Returns:
          List of paper dicts with: title, authors, abstract snippet,
          citations count, url, source.
      
      Example:
          search_google_scholar("climate change economic impact", max_results=5)
      """
      return await _search('google_scholar', query, max_results)

• paper_find_mcp/academic_platforms/google_scholar.py:94-143 (helper)

  Core implementation of the search logic in GoogleScholarSearcher class, performing HTTP requests to Google Scholar, parsing HTML with BeautifulSoup, and extracting paper metadata.

  def search(self, query: str, max_results: int = 10) -> List[Paper]:
      """
      Search Google Scholar with custom parameters
      """
      papers = []
      start = 0
      results_per_page = min(10, max_results)
  
      while len(papers) < max_results:
          try:
              # Construct search parameters
              params = {
                  'q': query,
                  'start': start,
                  'hl': 'en',
                  'as_sdt': '0,5'  # Include articles and citations
              }
  
              # Make request with random delay
              time.sleep(random.uniform(1.0, 3.0))
              response = self.session.get(self.SCHOLAR_URL, params=params)
              
              if response.status_code != 200:
                  logger.error(f"Search failed with status {response.status_code}")
                  break
  
              # Parse results
              soup = BeautifulSoup(response.text, 'html.parser')
              results = soup.find_all('div', class_='gs_ri')
  
              if not results:
                  break
  
              # Process each result
              for item in results:
                  if len(papers) >= max_results:
                      break
                      
                  paper = self._parse_paper(item)
                  if paper:
                      papers.append(paper)
  
              start += results_per_page
  
          except Exception as e:
              logger.error(f"Search error: {e}")
              break
  
      return papers[:max_results]

• paper_find_mcp/server.py:75-85 (registration)

  Instantiation and registration of GoogleScholarSearcher() in the global SEARCHERS dictionary, referenced by the _search helper function.

  SEARCHERS = {
      'arxiv': ArxivSearcher(),
      'pubmed': PubMedSearcher(),
      'biorxiv': BioRxivSearcher(),
      'medrxiv': MedRxivSearcher(),
      'google_scholar': GoogleScholarSearcher(),
      'iacr': IACRSearcher(),
      'semantic': SemanticSearcher(),
      'crossref': CrossRefSearcher(),
      'repec': RePECSearcher(),
  }

• paper_find_mcp/server.py:95-113 (helper)

  Generic _search helper function that invokes the specific searcher.search() method and converts Paper objects to dicts for the tool response.

  async def _search(
      searcher_name: str, 
      query: str, 
      max_results: int = 10,
      **kwargs
  ) -> List[Dict]:
      """通用搜索函数"""
      searcher = SEARCHERS.get(searcher_name)
      if not searcher:
          logger.error(f"Unknown searcher: {searcher_name}")
          return []
      
      try:
          papers = searcher.search(query, max_results=max_results, **kwargs)
          return [paper.to_dict() for paper in papers]
      except Exception as e:
          logger.error(f"Search failed for {searcher_name}: {e}")
          return []