AI Research MCP Server

Instructions

Implementation Reference

• src/ai_research_mcp/server.py:421-435 (handler)

  Handler function that executes the get_daily_papers tool logic: caches and formats papers fetched from HuggingFaceClient.get_daily_papers()
  async def _get_daily_papers(self, days: int = 1) -> str: """Get daily featured papers from Hugging Face.""" cache_key = f"hf_daily_{days}" cached = self.cache.get(cache_key, 3600 * 12) # 12 hour cache if cached: papers = cached else: papers = await asyncio.to_thread( self.huggingface.get_daily_papers, days=days, ) self.cache.set(cache_key, papers) return self._format_papers(papers)
• src/ai_research_mcp/server.py:121-134 (registration)

  Registration of the get_daily_papers tool in list_tools(), including input schema definition
  Tool( name="get_daily_papers", description="Get today's featured AI papers from Hugging Face", inputSchema={ "type": "object", "properties": { "days": { "type": "integer", "description": "Number of days to look back (1-7)", "default": 1, }, }, }, ),
• src/ai_research_mcp/data_sources/huggingface_client.py:49-95 (helper)

  Core helper function in HuggingFaceClient that fetches and processes daily papers from Hugging Face API endpoints.
  def get_daily_papers(self, days: int = 1) -> List[Dict]: """Get daily papers from Hugging Face. Args: days: Number of days to look back (1-7) Returns: List of paper dictionaries """ papers = [] for day_offset in range(days): date = datetime.now(timezone.utc) - timedelta(days=day_offset) date_str = date.strftime("%Y-%m-%d") try: url = f"{self.papers_base_url}?date={date_str}" response = requests.get(url, timeout=10) response.raise_for_status() daily_papers = response.json() for paper in daily_papers: # Ensure published date has timezone info published_date = paper.get("publishedAt", date_str) if published_date and "T" not in published_date: # If it's just a date, add time and timezone published_date = f"{published_date}T00:00:00+00:00" papers.append({ "title": paper.get("title", ""), "authors": paper.get("authors", []), "summary": paper.get("summary", ""), "published": published_date, "url": f"https://huggingface.co/papers/{paper.get('id', '')}", "arxiv_id": paper.get("id", ""), "upvotes": paper.get("upvotes", 0), "num_comments": paper.get("numComments", 0), "thumbnail": paper.get("thumbnail", ""), "source": "huggingface", }) except requests.RequestException as e: print(f"Error fetching papers for {date_str}: {e}") continue # Sort by upvotes papers.sort(key=lambda x: x.get("upvotes", 0), reverse=True) return papers