MCP AI Research Assistant
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP AI Research Assistantsummarize the article on renewable energy breakthroughs"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP AI Research Assistant (Offline)
📌 Overview
An offline AI Research Assistant built using the Model Context Protocol (MCP). The system uses a FastMCP server exposing structured tools and a custom client orchestrator communicating via stdio transport.
This project demonstrates end-to-end MCP integration without external APIs.
🚀 Features:
Summarize research text Extract key points Save research notes locally Retrieve saved notes Fully offline stdio-based MCP transport Structured tool invocation
🏗 Architecture
User CLI
↓
MCP Client
↓ (stdio transport)
FastMCP Server
↓
Tool Execution Layer
↓
notes.json🛠 Tech Stack:
Python 3.13
Model Context Protocol (MCP) v1.26.0
FastMCP
AsyncIO
▶️ How To Run:
Clone repository: git clone https://github.com/paneri11/mcp-ai-research-assistant.git
cd mcp-ai-research-assistant
Create virtual environment: python -m venv venv
venv\Scripts\activate # Windows
Install dependencies: pip install -r requirements.txt
Run: python client/client.py
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