substack-mcp
Enables engineering leaders running technical newsletters to programmatically manage content workflows, track subscriber engagement metrics, and automate pub…
MCP server for Substack: rich drafts, Notes, analytics, and consented subscriber management across publications. Long-form posts stay draft-only; Notes publish immediately. Used regularly by multiple newsletters, includes a CLI.
- Ask Claude to analyze subscriber engagement metrics across your Substack publications to identify top-performing content.
- Generate draft posts in Claude, then publish them directly to your Substack Notes for immediate distribution.
- Automate management of subscriber lists and preferences across multiple Substack publications from one interface.
Enables engineering leaders running technical newsletters to programmatically manage content workflows, track subscriber engagement metrics, and automate publishing—reducing manual overhead and improving content consistency across publications.
Technical newsletter operators and engineering communicators managing multiple Substack publications with analytics-driven content strategies.
https://github.com/conorbronsdon/substack-mcp
By conorbronsdon
How to Get It
claude mcp add substack-mcp -- npx -y substack-mcp
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:
Analyze subscriber engagement metrics across my Substack publications to identify top-performing content
Trust Signals Auto-scanned
Data & Access
Community Pulse Emerging
Discussed on Hacker News
- Every Substack, Mapped — Hacker News · 3 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 43 GitHub stars; contributors unknown; last commit 0d 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): 43 GitHub stars; contributors unknown; last commit 0d ago; license MIT.