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edisoncruz

Lenny's Wisdom MCP Server

by edisoncruz

Lenny's Wisdom MCP Server

License: MIT MCP LinkedIn

An MCP (Model Context Protocol) server providing structured access to wisdom from 20 curated Lenny's Podcast episodes featuring world-class product leaders.



Date: February 9, 2026
Status: MCP with highly adaptable foundation established. The remaining 280 transcripts will be extracted by the end of February 2026.


Why This Matters

We want to meet users where they are by making the collective wisdom of Lenny's tech titan guests available in your Claude, ChatGPT, or LLM of choice.

Instead of generic responses to prompts like "Look through these transcripts and give me frameworks about product-market fit" or "What does Brian Chesky have to say about prioritization?", this MCP server super-powers your LLM by augmenting its reasoning capabilities with the minds of the most successful leaders in tech.

Ask natural questions. Get specific, actionable advice from world-class PMsβ€”with context, timestamps, and quotes.


Features

πŸ” Core Tools (4)

  • search_wisdom(query) - Keyword search across all episodes

  • list_guests() - Browse all 20 available guests

  • get_episode(episode_id) - Get full episode details

  • search_by_topic(topic) - Filter by topic tags

🎯 Advanced Tools (5)

  • get_advice_for_situation(situation) - Get curated advice for specific PM challenges

  • get_actionable_insights(topic) - Filter for only immediately actionable tactics

  • compare_perspectives(topic, guests) - Compare how different leaders approach the same topic

  • get_quotes_by_guest(guest_name, topic) - Deep-dive into a specific leader's philosophy

  • list_frameworks() - Browse all frameworks (DHM, LNO, JTBD, Pre-mortems, etc.)

πŸ“š Episode Library (20 Episodes)

  1. Brian Chesky (Airbnb) - Founder mode, product obsession

  2. Claire Hughes Johnson (Stripe COO) - Scaling operations

  3. Matt Mochary (CEO Coach) - High output management

  4. Kim Scott - Radical Candor framework

  5. Gibson Biddle (Netflix VP Product) - DHM framework

  6. Shishir Mehrotra (Coda CEO) - Growth loops, Eigenquestions

  7. Shreyas Doshi (Stripe/Twitter) - Pre-mortems, LNO framework

  8. Casey Winters (Pinterest) - Kindle vs Fire strategies

  9. Dan Shipper (Every) - AI-first operations

  10. Ben Horowitz (a16z) - Running towards fear, managerial leverage

  11. Camille Fournier - Engineering management

  12. Ami Vora (Meta/WhatsApp) - Product leadership at scale

  13. Deb Liu (Ancestry CEO) - 30/60/90 onboarding

  14. April Dunford - Positioning frameworks

  15. Bob Moesta - Jobs to Be Done

  16. Annie Duke - Decision-making under uncertainty

  17. Bangaly Kaba (Instagram) - Growth loops

  18. Bret Taylor (ex-Salesforce Co-CEO) - Product-led growth

  19. Drew Houston (Dropbox) - Founder mode, scaling

  20. Dharmesh Shah (HubSpot) - Culture as product


Installation

Option 1: Claude Desktop or ChatGPT Desktop

1. Install the package:

pip install -e /path/to/lennys-wisdom-mcp

2. Configure Claude Desktop:

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "lennys-wisdom": {
      "command": "python",
      "args": ["/path/to/lennys-wisdom-mcp/lennys_wisdom/server.py"]
    }
  }
}

3. Restart Claude Desktop

Option 2: Claude Code or Cowork

Claude Code and Cowork automatically detect MCP servers installed via pip:

pip install -e /path/to/lennys-wisdom-mcp
# MCP server is now available in Claude Code/Cowork

Usage Examples

"I'm joining a new company as VP Product, what should I do?"
β†’ get_advice_for_situation() returns curated advice from multiple leaders

"Show me actionable insights about hiring"
β†’ get_actionable_insights() filters for immediately implementable advice

"How do Brian Chesky and Ben Horowitz approach leadership differently?"
β†’ compare_perspectives() shows side-by-side comparison

"What frameworks are available?"
β†’ list_frameworks() catalogs DHM, LNO, JTBD, Pre-mortems, etc.

Technical Overview

Architecture: FastMCP server with 9 tools accessing 280+ insights from 20 manually extracted episodes (~320,000 words processed)

Data Format: JSON files with 15 key insights per episode, including verbatim quotes, timestamps, themes with relevance scores, topic tags, frameworks, and actionable flags

Search: Keyword matching with relevance scoring

Output: Markdown-formatted responses

Extracted: February 2026 using Claude Sonnet 4.5


Contributing

Contributions welcome! Please submit a Pull Request.


Additional Resources

-
security - not tested
A
license - permissive license
-
quality - not tested

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