generate_weekly_summary

Create a weekly summary of AI research activity by aggregating papers, GitHub repositories, and Hugging Face models to track progress across multiple sources.

Instructions

Generate a comprehensive weekly summary of AI research activity

Input Schema

TableJSON Schema

Name	Required	Description
`include_papers`	No	Include papers section
`include_repos`	No	Include GitHub repos section
`include_models`	No	Include Hugging Face models section

Implementation Reference

src/ai_research_mcp/server.py:536-562 (handler)

The core handler function implementing the generate_weekly_summary tool logic: fetches weekly papers from multiple sources, trending repos, recent models, and formats into a markdown summary.

async def _generate_weekly_summary(
    self,
    include_papers: bool = True,
    include_repos: bool = True,
    include_models: bool = True,
) -> str:
    """Generate weekly summary."""
    sections = []
    sections.append(f"# AI Research Weekly Summary\n*Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}*\n")
    
    if include_papers:
        hf_papers = await asyncio.to_thread(self.huggingface.get_daily_papers, days=7)
        arxiv_papers = await asyncio.to_thread(self.arxiv.get_latest_papers, days=7, max_results=50)
        pwc_papers = await asyncio.to_thread(self.papers_with_code.get_latest_papers, days=7)
        
        all_papers = hf_papers + arxiv_papers + pwc_papers
        sections.append(f"## 📄 This Week's Papers ({len(all_papers)})\n\n{self._format_papers(all_papers[:30])}")
    
    if include_repos:
        repos = await asyncio.to_thread(self.github.get_trending_repositories, period="weekly", max_results=30)
        sections.append(f"## 🔥 Trending Repositories ({len(repos)})\n\n{self._format_repos(repos[:20])}")
    
    if include_models:
        models = await asyncio.to_thread(self.huggingface.get_recent_models, days=7, limit=25)
        sections.append(f"## 🤖 New & Updated Models ({len(models)})\n\n{self._format_models(models[:15])}")
    
    return "\n\n".join(sections)

src/ai_research_mcp/server.py:236-259 (registration)

Tool registration in list_tools() handler, defining the tool name, description, and input schema.

Tool(
    name="generate_weekly_summary",
    description="Generate a comprehensive weekly summary of AI research activity",
    inputSchema={
        "type": "object",
        "properties": {
            "include_papers": {
                "type": "boolean",
                "description": "Include papers section",
                "default": True,
            },
            "include_repos": {
                "type": "boolean",
                "description": "Include GitHub repos section",
                "default": True,
            },
            "include_models": {
                "type": "boolean",
                "description": "Include Hugging Face models section",
                "default": True,
            },
        },
    },
),

src/ai_research_mcp/server.py:239-259 (schema)

Input schema defining optional boolean parameters for including papers, repos, and models in the summary.

    inputSchema={
        "type": "object",
        "properties": {
            "include_papers": {
                "type": "boolean",
                "description": "Include papers section",
                "default": True,
            },
            "include_repos": {
                "type": "boolean",
                "description": "Include GitHub repos section",
                "default": True,
            },
            "include_models": {
                "type": "boolean",
                "description": "Include Hugging Face models section",
                "default": True,
            },
        },
    },
),

src/ai_research_mcp/server.py:280-281 (handler)
Dispatch logic in the main call_tool handler that invokes the weekly summary generator.
```
elif name == "generate_weekly_summary":
    result = await self._generate_weekly_summary(**arguments)
```

AI Research MCP Server