๐ง FastMCP SSE Server โ Research Paper Agent
@selinazarzour
About ๐ง FastMCP SSE Server โ Research Paper Agent
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Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-selinazarzour": {
"command": "uv",
"args": [
"pip",
"install",
"--system",
"."
]
}
}
}Tools
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is ๐ง FastMCP SSE Server โ Research Paper Agent?
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.
How to use ๐ง FastMCP SSE Server โ Research Paper Agent?
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.
Key features of ๐ง FastMCP SSE Server โ Research Paper Agent
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 folders- Prompt template for Claude to generate full topic reports
- Uses SSE transport for remote MCP client communication
Use cases of ๐ง FastMCP SSE Server โ Research Paper Agent
- Automate literature searches on arXiv for any research topic
- Build agent workflows that extract and store metadata from academic papers
- Generate structured research reports with Claude using the builtโin prompt template
FAQ from ๐ง FastMCP SSE Server โ Research Paper Agent
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.
What transport does it use?
It uses SSE (ServerโSent Events) transport, making it compatible with any MCP client that supports SSE.
What are the runtime requirements?
Python 3.11+, the uv package manager, and optionally Docker for deployment on Render.com.
How can I test the server locally or remotely?
Remotely, visit the live SSE URL or use the MCP Inspector (npx @modelcontextprotocol/inspector) with SSE transport and the serverโs URL. Locally, run uv run main.py and connect to localhost:8001/sse.
How is data stored?
Paper information is saved locally in a papers/ directory as JSON files when using search and extraction tools.
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