What does this server do?
It is an MCP remote server that provides tools to search arXiv papers, extract saved paper info, list topics, and generate structured prompts for LLMs.
@selinazarzour
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-selinazarzour": {
"command": "uv",
"args": [
"pip",
"install",
"--system",
"."
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A deployable MCP-compatible remote server built with FastMCP. It exposes tools for searching academic papers on arXiv, extracting saved paper details, and generating structured prompts for Claude or other LLM agents.
Connect any MCP client that supports SSE transport (e.g., Claude, GPT) to the live server at https://mcp-server-vs1x.onrender.com/sse. For local use, clone the repo, install dependencies with uv, and run uv run main.py to start the server on localhost:8001/sse.
search_papers(topic): Search and save top arXiv papers by topicextract_info(paper_id): Retrieve paper details from stored JSONget_topic_papers(topic): Read summaries for all papers in a topicget_available_folders(): List all saved topic foldersIt is an MCP remote server that provides tools to search arXiv papers, extract saved paper info, list topics, and generate structured prompts for LLMs.
It uses SSE (Server‑Sent Events) transport, making it compatible with any MCP client that supports SSE.
Python 3.11+, the `uv` package manager, and optionally Docker for deployment on Render.com.
Remotely, visit the live SSE URL or use the MCP Inspector (`npx @modelcontextprotocol/inspector`) with SSE transport and the server’s URL. Locally, run `uv run main.py` and connect to `localhost:8001/sse`.
Paper information is saved locally in a `papers/` directory as JSON files when using search and extraction tools.
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