notion-memory-mcp
Enables AI agents to use Notion as a persistent memory tier by providing tools to search, read, save (upsert) pages, append to pages, and query databases.
README
Notion Memory MCP 🧠
A Model Context Protocol server that turns Notion into a programmable memory tier for AI agents.
Give any MCP-compatible agent (Hermes, Claude Desktop, Cursor, custom agents) five clean tools to search, read, save, append, and query your Notion workspace — making Notion the persistent "disk" layer of an agent's 3-tier memory architecture.
⚡ L1 cache → agent built-in memory (always in context)
🧮 RAM → mem0 / vector store (auto recall)
💾 DISK → Notion via this MCP ← you are here
Why
Agent memory solutions (mem0, honcho...) are opaque — great for reflexive recall, invisible to humans. Notion is the opposite: fully visible and editable by humans, but not natively tool-callable.
This server bridges them: agents get programmatic access; humans keep full visual control.
Tools exposed
| Tool | What it does |
|---|---|
notion_search(query) |
Find pages/databases by title or content |
notion_read(page_id) |
Read a page as structured plain text |
notion_save(title, content) |
Upsert page by exact title (markdown-ish → blocks) |
notion_append(page_id, text) |
Append to a page (running logs) |
notion_query_db(db_id) |
Query database rows with optional select-filter |
Setup
pip install -r requirements.txt
export NOTION_API_TOKEN=ntn_your_integration_token # notion.so/my-integrations
python3 server.py # stdio transport
Hermes Agent
hermes mcp add notion-memory -- python3 /path/to/server.py
# with env: NOTION_API_TOKEN set in ~/.hermes/.env
Claude Desktop / Cursor
Add to your MCP config:
{
"mcpServers": {
"notion-memory": {
"command": "python3",
"args": ["/path/to/server.py"],
"env": { "NOTION_API_TOKEN": "ntn_..." }
}
}
}
Design decisions
- Upsert-by-title (
notion_save): agents think in names, not UUIDs. Re-saving replaces the body — idempotent writes. - Markdown-ish → blocks: headings (#), bullets (-), paragraphs map to native Notion blocks. No complex AST.
- Read-open, write-scoped: reads hit whatever the integration can see; create/update only. No delete tool by design — destructive ops stay human-only.
- stdlib + httpx + mcp: minimal dependencies, easy audit.
Skills demonstrated
MCP server development · async Python (httpx + asyncio) · Notion API (search/blocks/databases) · protocol design for LLM tool use · defensive API error mapping
License
MIT — built by Shahjalal Shanto
Part of an agent-memory architecture: built-in cache + mem0 RAM + Notion disk.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。