ResearchMCP

# ResearchMCP - AI-Powered Research Paper Assistant An MCP (Model Context Protocol) server that helps analyze academic papers by fetching research from OpenAlex's database of 250M+ papers. ## Features - **Search Papers**: Search for academic papers by topic/keywords with advanced filtering - **Extract Claims**: Automatically extract key findings and research claims from papers - **Compare Papers**: Identify contradictions and consensus across multiple papers - **Citation Analysis**: Explore citation networks to discover related research - **Research Gap Finder**: Analyze multiple papers to identify gaps and future research opportunities - Powered by OpenAlex API (millions of papers, no API key needed!) ## Tools ### `search_papers` Search for academic papers on OpenAlex. **Parameters:** - `query` (string, required): Research topic or keywords - `max_results` (int, optional): Maximum papers to return (default: 5) - `year_from` (int, optional): Only papers from this year onwards **Example:** "Search for papers on transformer models in NLP" ### `get_paper_abstract` Get the full abstract for a specific paper. **Parameters:** - `paper_id` (string, required): OpenAlex paper ID from search results **Example:** "Get abstract for paper W2964027837" ### `extract_claims` Extract key claims and findings from a paper's abstract. **Parameters:** - `paper_id` (string, required): OpenAlex paper ID **Returns:** Structured extraction of research questions, methodology, findings, and conclusions **Example:** "Extract claims from paper W2964027837" ### `compare_papers` Compare claims across multiple papers to find contradictions and consensus. **Parameters:** - `paper_ids` (string, required): Comma-separated list of paper IDs (2-5 papers) **Returns:** Comparative analysis showing agreements, contradictions, and research gaps **Example:** "Compare these papers: W2964027837, W3177828909, W2123456789" ### `get_citations` Get citation network for a paper - see what cites it and what it references. **Parameters:** - `paper_id` (string, required): OpenAlex paper ID - `direction` (string, optional): "cited_by", "references", or "both" (default: "both") - `max_results` (int, optional): Maximum citations per direction (default: 10) **Returns:** Lists of papers that cite this work and papers it references **Example:** "Show me the citation network for W2964027837" ### `find_research_gaps` Analyze multiple papers on a topic to identify research gaps and unanswered questions. **Parameters:** - `query` (string, required): Research topic to analyze - `num_papers` (int, optional): Number of papers to analyze (default: 5, max: 10) **Returns:** Comprehensive gap analysis including: - Unanswered research questions - Methodological limitations - Understudied areas - Contradictions requiring further investigation - Emerging research opportunities **Example:** "Find research gaps in transformer architecture optimization" ## Installation ### Option 1: Deploy to FastMCP Cloud (Recommended) 1. Clone the repository: ```bash git clone https://github.com/YOUR_USERNAME/ResearchMCP.git cd ResearchMCP ``` 2. Deploy to FastMCP Cloud: ```bash fastmcp deploy ``` 3. Set the entrypoint as: `src/server.py` 4. Connect to Claude Desktop by adding to your MCP settings ### Option 2: Run Locally ```bash # Clone the repository git clone https://github.com/YOUR_USERNAME/ResearchMCP.git cd ResearchMCP # Install dependencies uv sync # Run the server uv run src/server.py ``` ## Usage with Claude Desktop Once deployed or running locally, you can use natural language prompts in Claude Desktop: **Search for papers:** - "Search for recent papers on quantum computing" - "Find papers about CRISPR gene editing from 2020 onwards" **Analyze specific papers:** - "Extract the key claims from paper W2964027837" - "Get the abstract for paper W3177828909" **Compare research:** - "Compare these papers: W2964027837, W3177828909" - "What do these papers agree and disagree on?" **Explore citations:** - "Show me what papers cite W2964027837" - "What papers does W2964027837 reference?" **Find research gaps:** - "Find research gaps in transformer architecture optimization" - "What are the unanswered questions in climate change modeling?" ## Architecture ResearchMCP uses a clean separation of concerns architecture: - **[server.py](src/server.py)**: MCP server that defines tools available to Claude Desktop - **[paper_fetcher.py](src/tools/paper_fetcher.py)**: Worker class handling all OpenAlex API interactions This design pattern ensures: - Clean code organization - Easy maintenance and testing - Separation between tool orchestration and API logic ## Technology Stack - **FastMCP**: Python framework for building MCP servers - **OpenAlex API**: Access to 250M+ academic papers with no API key required - **httpx**: Modern async-capable HTTP client - **Python 3.12+**: Type hints and modern Python features ## Why MCP over RAG? Traditional RAG systems require: - Pre-indexing large document collections - Vector database setup and maintenance - Embedding generation costs - Limited to pre-indexed documents ResearchMCP with MCP: - **Live access** to 250M+ papers without pre-indexing - **No infrastructure** - no vector databases needed - **Always up-to-date** - accesses latest published research - **Cost-effective** - no embedding generation costs - **Tool orchestration** - Claude intelligently chains multiple API calls ## Contributing Contributions are welcome! Feel free to submit issues or pull requests. ## License MIT License - feel free to use this project for your research needs!