NotionMCP

NotionMCP

Enables AI assistants to search, read, summarize, and analyze sentiment of Notion pages and databases, turning your Notion workspace into an intelligent, queryable knowledge system.

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README

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 ./demo/1.mp4

Image Walkthrough


Installation

You may install using either:

Option A — Using venv (recommended for most users)

1. Clone the repository

git clone https://github.com/DeepActionPotential/NotionMCP.git
cd NotionMCP

2. Create and activate a virtual environment

python -m venv .venv

Activate it:

Windows

.venv\Scripts\activate

macOS/Linux

source .venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Run the MCP server

python server.py

Option B — Installation using uv

uv sync
uv run server.py

Configuring Claude Desktop

Add the following to:

claude_desktop_config.json

{
  "mcpServers": {
    "NotionMCPServer": {
      "command": "uv",
      "args": [
        "--directory",
        "your-own-server-file-directory",
        "run",
        "server.py"
      ]
    }
  }
}

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:

NOTION_API_KEY=secret_notion-api
HTTP-TIMEOUT=60

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

NotionMCP
│
├── tools/
│   ├── search_tools.py
│   ├── read_tools.py
│   └── ai_tools.py
│
├── core/
│   └── notion_clients.py
│
├── services/
│   ├── summarization_service.py
│   └── text_emotion_service.py
│
├── demo/
│
└── server.py

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.

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