What is Mcp Bases

mcp-bases is a powerful research assistant built using the Model Context Protocol (MCP) that facilitates the search, analysis, and organization of academic papers from arXiv.

Use cases

Use cases include searching for specific academic papers, summarizing research trends, organizing papers by topic, and interacting with an AI assistant for research assistance.

How to use

To use mcp-bases, clone the repository, install the required dependencies, set up your environment with the Anthropic API key, and start the research assistant by running the chatbot script. You can interact with the chatbot using natural language queries.

Key features

Key features include paper search via arXiv’s API, automatic organization of papers by topic, detailed information extraction (title, authors, publication date, summary, PDF URL), an interactive chat interface for research queries, and comprehensive research analysis.

Where to use

mcp-bases can be used in academic research, educational institutions, and by individual researchers who need to manage and analyze large volumes of academic literature.

MCP Research Assistant

A powerful research assistant built using the Model Context Protocol (MCP) that helps users search, analyze, and organize academic papers from arXiv.

Features

• Paper Search: Search for academic papers on any topic using arXiv’s API
• Paper Organization: Automatically organize papers by topic in a structured format
• Paper Information Extraction: Extract and store detailed information about papers including:
  • Title
  • Authors
  • Publication date
  • Summary
  • PDF URL
• Interactive Chat Interface: Chat with an AI assistant to help with your research queries
• Topic-based Organization: Papers are automatically organized into topic-based folders
• Comprehensive Research Analysis: Get summaries and analysis of research trends in your area of interest

Prerequisites

• Python 3.x (used 3.12.8)
• Node.js and npm (used v22.13.0)
• Anthropic API key

Installation

1. Clone the repository:

git clone https://github.com/ezequiroga/mcp-bases
cd mcp-bases

2. Install Python dependencies:

pip install -r requirements.txt

3. Copy the environment file and add your API key:

cp .env-example .env
# Edit .env and add your Anthropic API key

4. Update npm

npm install -g npm@latest

Project Structure

• research_server.py: Main server implementation for paper search and management
• mcp_chatbot.py: Interactive chatbot implementation
• server_config.json: Configuration for MCP servers
• papers/: Directory where paper information is stored (created automatically)

Usage

1. Start the research assistant:

python mcp_chatbot.py

2. Interact with the chatbot using natural language queries. For example:

   • “Search for papers about quantum computing”
   • “What are the latest papers on machine learning?”
   • “Summarize the research on artificial intelligence”

3. Finish the chatbot by typing quit.

Available Tools

The system provides several tools through the MCP interface:

• search_papers: Search for papers on a specific topic
• extract_info: Get detailed information about a specific paper
• get_available_folders: List all available topic folders
• get_topic_papers: Get detailed information about papers in a specific topic

Configuration

The server_config.json file configures three MCP servers:

• filesystem: For file system operations
• research: The main research server
• fetch: For fetching operations