Notion Chakra MCP
@thestumonkey
关于 Notion Chakra MCP
fastmcp implementation of notion-mcp server with support for extensible custom objects and functions
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"notion-chakra-mcp": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-v",
"/path/to/notion-chakra-mcp/data:/app/data",
"-e",
"TRANSPORT",
"-e",
"NOTION_API_KEY",
"-e",
"HOST",
"-e",
"PORT",
"-e",
"PYTHONPATH=/app/src",
"notion-chakra-mcp"
],
"env": {
"TRANSPORT": "stdio",
"NOTION_API_KEY": "your_notion_api_key",
"HOST": "0.0.0.0",
"PORT": "8050"
}
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Notion Chakra MCP?
Notion Chakra MCP is a Notion integration service that provides MCP (Message Control Protocol) endpoints for interacting with Notion databases and pages. It supports both stdio and SSE transports and is intended for developers using MCP clients like Cursor.
How to use Notion Chakra MCP?
Configure Notion Chakra MCP as an MCP server in your client’s mcp.json (e.g., ~/.cursor/mcp.json), using a Docker container. Set the NOTION_API_KEY environment variable and optionally choose stdio or sse transport. Alternatively, use Docker Compose or direct Docker commands. A data directory must exist for persistence.
Key features of Notion Chakra MCP
- List and query Notion databases
- Create and update Notion pages
- Search Notion content
- Manage blocks and children
- Support for both stdio and SSE transports
Use cases of Notion Chakra MCP
- Query Notion databases programmatically via MCP tools
- Create or update pages in Notion from an MCP client
- Search across Notion workspaces
- Manage hierarchical block content
FAQ from Notion Chakra MCP
What environment variables are required?
NOTION_API_KEY is required. Optional variables include TRANSPORT (stdio or sse), HOST, PORT, and PYTHONPATH.
How can I choose between stdio and SSE transport?
Set the TRANSPORT environment variable to stdio or sse. The default is stdio.
How is data persisted?
A data directory must be mounted at /app/data inside the container. It stores schemas, database mappings, and other persistent data.
How do I run the tests?
Install test dependencies with pip install -r requirements.txt, then run python -m pytest tests/ -v.
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