Content
# 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.
Connection Info
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