notion-mcp-server
Integrates Notion into AI workflows, eliminating manual context-switching and enabling Claude to read/write documentation, requirements, and decision logs di…
Community-built MCP server (awkoy) that connects AI assistants to Notion's API — read and update pages, query databases and tasks, and write generated content such as meeting notes directly into your workspace. An independent alternative to the official makenotion server.
- Ask Claude to pull project status updates from your Notion database and summarize them
- Generate meeting notes directly into a Notion page from Claude's analysis
- Find overdue tasks in your Notion workspace and create a priority report
Integrates Notion into AI workflows, eliminating manual context-switching and enabling Claude to read/write documentation, requirements, and decision logs directly within your knowledge base.
Engineering teams using Notion as source-of-truth for specifications, runbooks, and project tracking.
https://github.com/awkoy/notion-mcp-server
By awkoy
How to Get It
claude mcp add notion-mcp-server -- npx -y notion-mcp-server
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Pull project status updates from my Notion database and summarize them
Trust Signals Auto-scanned
Data & Access
Community Pulse Quiet
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 151 GitHub stars; contributors unknown; last commit 7d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 151 GitHub stars; contributors unknown; last commit 7d ago; license MIT.