Notion ReadOnly MCP Server

This project implements an optimized read-only MCP server for the Notion API, focusing on performance and efficiency for AI assistants to query and retrieve Notion content.

<a href="https://glama.ai/mcp/servers/@Taewoong1378/notion-readonly-mcp-server">

</a>

Key Improvements

- Read-Only Design: Focused exclusively on data retrieval operations, ensuring safe access to Notion content.
- Minimized Tool Set: Reduced the number of exposed Notion API tools from 15+ to only 6 essential ones for document analysis.
- Parallel Processing: Enhanced performance by implementing asynchronous and parallel API requests for retrieving block content, significantly reducing response times.
- Extended Database Access: Added support for database, page property, and comment retrieval operations.
- Optimized for AI Assistants: Significantly reduced tool count addresses the "Too many tools can degrade performance" issue in AI assistants like Cursor, which limits models to approximately 40 tools.

Tool Comparison

This read-only implementation exposes far fewer tools compared to the standard Notion API integration, improving performance and compatibility with AI assistants:

The reduced tool set helps stay within the recommended tool limits for optimal AI assistant performance while still providing all essential functionality.

Installation

1. Setting up Integration in Notion:

Go to https://www.notion.so/profile/integrations and create a new internal integration or select an existing one.

While we limit the scope of Notion API's exposed to read-only operations, there is a non-zero risk to workspace data by exposing it to LLMs. Security-conscious users may want to further configure the Integration's _Capabilities_.

For example, you can create a read-only integration token by giving only "Read content" access from the "Configuration" tab:

2. Adding MCP config to your client:

Using npm:

Add the following to your .cursor/mcp.json or claude_desktop_config.json (MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json)

{
  "mcpServers": {
    "notionApi": {
      "command": "npx",
      "args": ["-y", "notion-readonly-mcp-server"],
      "env": {
        "OPENAPI_MCP_HEADERS": "{\"Authorization\": \"Bearer ntn_*\", \"Notion-Version\": \"2022-06-28\" }"
      }
    }
  }
}

{
  "mcpServers": {
    "notionApi": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e", "OPENAPI_MCP_HEADERS",
        "taewoong1378/notion-readonly-mcp-server"
      ],
      "env": {
        "OPENAPI_MCP_HEADERS": "{\"Authorization\":\"Bearer ntn_\",\"Notion-Version\":\"2022-06-28\"}"
      }
    }
  }
}

- Recursive retrieval: Automatically traverses the entire page structure including nested blocks
- Parallel processing: Fetches multiple blocks and their children simultaneously for maximum performance
- Intelligent caching: Stores retrieved data to minimize redundant API calls
- Comprehensive content: Includes pages, blocks, databases, comments, and detailed property information
- Customizable depth*: Control the level of recursion to balance between detail and performance

Using One Pager Tool

{
  "page_id": "YOUR_PAGE_ID",
  "maxDepth": 5,               // Optional: Maximum recursion depth (default: 5)
  "includeDatabases": true,    // Optional: Include linked databases (default: true)
  "includeComments": true,     // Optional: Include comments (default: true)
  "includeProperties": true    // Optional: Include detailed page properties (default: true)
}

This automatic exploration capability is especially useful for AI assistants that need to understand the entire content of a Notion page without making dozens of separate API calls, resulting in much faster and more efficient responses.

Asynchronous Processing

The server implements advanced parallel processing techniques for handling large Notion documents:

- Multiple requests are batched and processed concurrently
- Pagination is handled automatically for block children
- Results are efficiently aggregated before being returned
- Console logging provides visibility into the process without affecting response format

Examples

1. Using the following instruction:

Get the content of page 1a6b35e6e67f802fa7e1d27686f017f2

The AI will retrieve the page details efficiently with parallel processing of block content.

2. Using database information:

Get the structure of database 8a6b35e6e67f802fa7e1d27686f017f2

Development

Build:

pnpm build

Execute:

pnpm dev

License

MIT

AI Assistant Performance Benefits

Modern AI assistants like Cursor and Claude have limitations on the number of tools they can effectively handle:

- Most models may not respect more than 40 tools in total
- Too many tools can degrade overall performance and reasoning capabilities
- Complex tool sets increase response latency and decision-making difficulty

This read-only implementation deliberately reduces the Notion API surface to address these limitations while preserving all essential functionality. The result is:

- Faster and more reliable responses from AI assistants
- Improved accuracy when interacting with Notion content
- Better overall performance through focused API design