arxiv_paper_mcp

# Arxiv Paper MCP Server <img src="./resource/arxiv_mcp_icon.png" width="500" height="500"> MCP(Model Context Protocol) server can search papersfrom arxiv api. ## 1. Pre-Required 1. Google llm api key : This mcp server use google llm(gemini series). So generate google llm api key first. 2. Select using model : This mcp server initialize llm model by langchain's [init_chat_model](https://python.langchain.com/api_reference/langchain/chat_models/langchain.chat_models.base.init_chat_model.html) function. Follow this format **"{model_provider}:{model_name}"**; Example value "google_genai:gemini-2.0-flash". ## 2. Installation ### Cursor ```sh uv sync source .venv/bin/activate # generate mcp.json setting python -m src.setup.cursor \ -e GOOGLE_API_KEY=<YOUR GOOGLE LLM API KEY> \ -e USING_MODEL_INFO=<YOUR USING MODEL INFO> \ -e MODEL_TEMPERATURE=0.0 \ -e MODEL_SEED=256 ``` ## 3. Support Tool ### a. search_papers_based_user_query Search papers from Arxiv API that user want to search. **Example** ``` Q: I want to search recent papers in NLP domain. ``` <img src="./resource/search_papers_based_user_query_tool_example.png" width="550"> ### b. paper_download_tool Download paper by user given arxiv id. **Example** ``` Q: Download 1706.03762 paper. ``` <img src="./resource/download_paper_tool.png" width="550"> ### c. return_section_names_tool Return section names of target paper. **Example** ``` Q: showing section of 1706.03762 paper to me. ``` <img src="./resource/paper_section_names_tool.png" width="550"> ### d. description_paper_content Descrive paper content and section from user question. **Example** ``` Q: Descrive "Model Architecture" section to me. ``` <img src="./resource/descrive_paper_tool.png" width="550"> ## 4. License This project is open source software licensed as MIT.