AI prompts
base on A Model Context Protocol server for searching and analyzing arXiv papers [](https://twitter.com/JoeBlazick)
[](https://smithery.ai/server/arxiv-mcp-server)
[](https://www.python.org/downloads/)
[](https://github.com/blazickjp/arxiv-mcp-server/actions/workflows/tests.yml)
[](https://opensource.org/licenses/MIT)
[](https://pypi.org/project/arxiv-mcp-server/)
[](https://pypi.org/project/arxiv-mcp-server/)
# ArXiv MCP Server
> 🔍 Enable AI assistants to search and access arXiv papers through a simple MCP interface.
The ArXiv MCP Server provides a bridge between AI assistants and arXiv's research repository through the Model Context Protocol (MCP). It allows AI models to search for papers and access their content in a programmatic way.
<div align="center">
🤝 **[Contribute](https://github.com/blazickjp/arxiv-mcp-server/blob/main/CONTRIBUTING.md)** •
📝 **[Report Bug](https://github.com/blazickjp/arxiv-mcp-server/issues)**
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</div>
## ✨ Core Features
- 🔎 **Paper Search**: Query arXiv papers with filters for date ranges and categories
- 📄 **Paper Access**: Download and read paper content
- 📋 **Paper Listing**: View all downloaded papers
- 🗃️ **Local Storage**: Papers are saved locally for faster access
- 📝 **Prompts**: A Set of Research Prompts
## 🚀 Quick Start
### Installing via Smithery
To install ArXiv Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/arxiv-mcp-server):
```bash
npx -y @smithery/cli install arxiv-mcp-server --client claude
```
### Installing Manually
Install using uv:
```bash
uv tool install arxiv-mcp-server
```
For development:
```bash
# Clone and set up development environment
git clone https://github.com/blazickjp/arxiv-mcp-server.git
cd arxiv-mcp-server
# Create and activate virtual environment
uv venv
source .venv/bin/activate
# Install with test dependencies
uv pip install -e ".[test]"
```
### 🔌 MCP Integration
Add this configuration to your MCP client config file:
```json
{
"mcpServers": {
"arxiv-mcp-server": {
"command": "uv",
"args": [
"tool",
"run",
"arxiv-mcp-server",
"--storage-path", "/path/to/paper/storage"
]
}
}
}
```
For Development:
```json
{
"mcpServers": {
"arxiv-mcp-server": {
"command": "uv",
"args": [
"--directory",
"path/to/cloned/arxiv-mcp-server",
"run",
"arxiv-mcp-server",
"--storage-path", "/path/to/paper/storage"
]
}
}
}
```
## 💡 Available Tools
The server provides four main tools:
### 1. Paper Search
Search for papers with optional filters:
```python
result = await call_tool("search_papers", {
"query": "transformer architecture",
"max_results": 10,
"date_from": "2023-01-01",
"categories": ["cs.AI", "cs.LG"]
})
```
### 2. Paper Download
Download a paper by its arXiv ID:
```python
result = await call_tool("download_paper", {
"paper_id": "2401.12345"
})
```
### 3. List Papers
View all downloaded papers:
```python
result = await call_tool("list_papers", {})
```
### 4. Read Paper
Access the content of a downloaded paper:
```python
result = await call_tool("read_paper", {
"paper_id": "2401.12345"
})
```
## 📝 Research Prompts
The server offers specialized prompts to help analyze academic papers:
### Paper Analysis Prompt
A comprehensive workflow for analyzing academic papers that only requires a paper ID:
```python
result = await call_prompt("deep-paper-analysis", {
"paper_id": "2401.12345"
})
```
This prompt includes:
- Detailed instructions for using available tools (list_papers, download_paper, read_paper, search_papers)
- A systematic workflow for paper analysis
- Comprehensive analysis structure covering:
- Executive summary
- Research context
- Methodology analysis
- Results evaluation
- Practical and theoretical implications
- Future research directions
- Broader impacts
## ⚙️ Configuration
Configure through environment variables:
| Variable | Purpose | Default |
|----------|---------|---------|
| `ARXIV_STORAGE_PATH` | Paper storage location | ~/.arxiv-mcp-server/papers |
## 🧪 Testing
Run the test suite:
```bash
python -m pytest
```
## 📄 License
Released under the MIT License. See the LICENSE file for details.
---
<div align="center">
Made with ❤️ by the Pearl Labs Team
<a href="https://glama.ai/mcp/servers/04dtxi5i5n"><img width="380" height="200" src="https://glama.ai/mcp/servers/04dtxi5i5n/badge" alt="ArXiv Server MCP server" /></a>
</div>
", Assign "at most 3 tags" to the expected json: {"id":"13276","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"