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Cover image for Auto-Researcher Hub: Bridging AI Knowledge and Workspace Automation
Hala Kabir
Hala Kabir

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Auto-Researcher Hub: Bridging AI Knowledge and Workspace Automation

Notion MCP Challenge Submission 🧠

This is a submission for the Notion MCP Challenge

What I Built
The Auto-Researcher Hub is an agentic workspace architect designed to solve the "blank page" problem in high-velocity research. As an AI and Blockchain developer, I often find myself overwhelmed with technical papers and scattered documentation.

I built a system that doesn't just "talk" about research but physically builds the environment for it. Using a Python-based orchestration layer, the tool automatically constructs a structured Research Database in Notion, complete with custom properties (Summary, URL, Status), and populates it with verified data points on Multi-Agent Systems and ZK-Proofs.

Video Demo
Watch the Auto-Researcher Hub in action here!

Show us the code
The full source code, including the orchestration script and the README, can be found here:

GitHub Repository: notion-auto-researcher

How I Used Notion MCP
Integrating the Notion Model Context Protocol (MCP) was a game-changer for my workflow. Traditionally, chatbots are "trapped" in a chat bubble; they can tell you what to do, but they can't do it for you.

By using the Notion MCP server (specifically @modelcontextprotocol/server-notion), I unlocked the ability for an AI agent to:

Architect Schemas: Use Python logic to define exactly what a "Research Database" should look like.

Contextual Awareness: The agent can "see" my existing Notion pages and decide where to build the hub.

Automated Population: It bridges the gap between raw web data and structured productivity, turning a manual 15-minute setup task into a 5-second automated execution.

This integration transforms Notion from a passive notebook into an active, collaborative partner that can organize my thoughts before I even start typing.

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