NotionMCP — AI-Powered Notion Assistant via MCP

NotionMCP is a Modular Context Protocol (MCP) server that exposes advanced Notion search, reading, summarization, and emotion-analysis tools to any MCP-compatible LLM client such as Claude Desktop.

This project turns your Notion workspace into an intelligent, queryable knowledge system, giving your AI assistant the ability to:

• Search pages and databases with precision

• Read and extract block-level content

• Summarize large or complex Notion pages

• Analyze sentiment/emotion of page text

• Build AI workflows on top of your Notion data

• Operate securely using the MCP standard

It is built for:

• Developers

• Researchers

• Data science teams

• Knowledge-intensive organizations

• Anyone wanting an AI agent deeply integrated with Notion

Features

Intelligent Notion Search

• Title search

• Page/database filtering

• Pagination + streaming search

• User discovery tools

Advanced Content Reading

• Extract readable text from pages

• Traverse block structures

• Read pages by name or ID

• Support for headings, lists, checkboxes, callouts, quotes, etc.

AI Summaries & Emotion Analysis

• Abstractive summarization (T5)

• Emotion/tone classification (Transformers)

• Integrated into Notion workflows

Fully MCP-Compatible

Works out-of-the-box with:

• Claude Desktop

• ChatGPT MCP mode

• Any MCP-compatible automation or agent

Clean, Modular Architecture

• search_tools.py

• read_tools.py

• ai_tools.py

• Async Notion client layer with retries + rate-limit handling

Business Value

NotionMCP upgrades Notion from a documentation space into a scalable AI knowledge engine. It enables teams and organizations to operate faster, reduce manual overhead, and make better decisions by turning unstructured notes into actionable intelligence.

For Organizations

• Automate summarization, research, onboarding, and documentation workflows

• Improve knowledge accessibility across teams and departments

• Standardize how information is consumed, summarized, and shared

• Reduce operational time spent searching or rewriting content

• Build internal AI agents capable of retrieving, processing, and analyzing company knowledge

For Technical Teams

• Gain a robust async Notion API client with retry + backoff handling

• Extend MCP tools with custom AI models or internal logic

• Integrate Notion into broader AI, analytics, or automation pipelines

• Build reproducible and automated workflows on top of Notion pages

• Maintain full control over data by running tools locally

Strategic Outcomes

• Faster decision-making

• Reduced cognitive load across technical and non-technical teams

• Stronger organizational memory and knowledge consistency

• A foundation for deployable AI assistants operating on real company data

Demo

Video Demo

Click to view

Image Walkthrough

Installation

You may install using either:

Option A — Using

1. Clone the repository

2. Create and activate a virtual environment

Activate it:

Windows

macOS/Linux

3. Install dependencies

4. Run the MCP server

Option B — Installation using

Configuring Claude Desktop

Add the following to:

claude_desktop_config.json

Restart Claude Desktop. You should now see all Notion tools available under the MCP Tools menu.

Environment Variables

Create a .env file or export environment variables:

Your Notion integration must be shared with the pages or workspace you want to read.

Usage Examples

Ask Claude:

• “Search Notion for pages about convolution.”

• “Summarize the Deep Learning page in 200 words.”

• “Extract the first 20 lines of the Metrics page.”

• “Analyze the emotional tone of the Vision page.”

Claude will automatically call MCP tools such as:

• search

• iter_search

• get_page_text

• summarize_page_text

• get_page_sentiment

Architecture

Contributing

Contributions are welcome:

• New AI models

• Additional Notion endpoints

• Performance improvements

• New MCP tools

Please open an issue or submit a PR.

License

MIT License — free for commercial and private use.