Mikensey MCP Server
Enables analysis of Zillow's strategy through transcript search and consulting frameworks, allowing users to understand competitive positioning and strategic insights from industry discussions.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Mikensey MCP Serveranalyze my brokerage's situation using a 2×2 matrix — we're losing agents to cloud brokerages"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Mikensey MCP Server
McKinsey-style strategy intelligence for real estate — powered by 53 episodes of Mike DelPrete's Context podcast.
An open-source MCP server that gives Claude (or any MCP-compatible AI) access to real estate industry benchmarks, consulting frameworks, and full-text transcript search. Ask it to analyze your business situation using 2×2 matrices, SCR memos, issue trees, or Porter's Five Forces — grounded in real data from industry leaders.
Tools
Tool | What it does |
| Full-text search across all 53 transcripts |
| Browse and filter episodes by guest or topic |
| Read full or partial transcripts |
| Query 26 industry benchmarks (attach rates, costs, growth metrics) |
| Browse 10 industry frameworks + 6 consulting frameworks |
| Apply a consulting framework (2×2, SCR, Issue Tree, Porter's, Value Chain, MECE) to your situation |
| SCR-structured strategy brief combining search, benchmarks, and frameworks |
Quick Start
git clone https://github.com/YOUR_USERNAME/mikensey-mcp-server.git
cd mikensey-mcp-server
npm install
npm run buildAdd to Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json on Mac):
{
"mcpServers": {
"mikensey": {
"command": "node",
"args": ["/path/to/mikensey-mcp-server/dist/index.js"],
"env": {
"MIKENSEY_TRANSCRIPT_DIR": "/path/to/your/transcript-files"
}
}
}
}Restart Claude Desktop. You'll see "mikensey" in the tools menu.
Usage
Just talk to Claude naturally:
"Analyze my situation using a 2×2 matrix — I'm a broker losing agents to cloud brokerages"
"Give me an SCR strategy memo — I'm a mortgage LO worried about AI replacing my job"
"Build an issue tree for how a proptech startup can achieve profitability"
"What are the benchmark attach rates for mortgage in real estate?"
"Which episodes cover Zillow's strategy?"
What's Inside
26 industry benchmarks — specific numbers cited by leaders like Tamir Poleg (Real), Glenn Sanford (eXp), Garth Graham (Stratmore), Justin Messer (Prosperity), and more. Attach rates, origination costs, agent productivity, growth metrics.
10 industry frameworks — mental models from the podcast: the 3-Lever Consumer Value Model, the Brokerage Pretzel, the Agent Value Equation, Hand-to-Hand Combat, W-H-Y sales framework, and more.
6 consulting frameworks — McKinsey-style analytical tools: 2×2 Matrix, Situation-Complication-Resolution (SCR), Issue Trees (MECE), Porter's Five Forces, Value Chain Analysis, and MECE Breakdowns. Each comes with real estate examples and pre-built templates.
4 pre-built 2×2 matrices — Brokerage Business Models, Mortgage Origination Strategy, Proptech Startup Survival, Agent Recruitment & Retention — with companies plotted and insights synthesized from transcript evidence.
3 pre-built issue trees — Brokerage Profitability, Mortgage Growth Strategy, Proptech Product-Market Fit — with MECE branches and supporting data.
Transcript Format
The server expects .txt files named like:
YYYY-MM-DD_guest-name-episode-title.txtFor example: 2024-03-15_varun-krishna-rockets-next-chapter.txt
Configuration
Environment Variable | Default | Description |
|
| Path to folder with |
Development
npm run dev # Watch mode with tsx
npm run build # Compile TypeScript
npm start # Run compiled serverBYO Transcripts
This server works with any set of transcripts in the expected format. You could adapt it to your own podcast, interview series, or research corpus — just point MIKENSEY_TRANSCRIPT_DIR at your files.
Cost
Zero. Runs entirely locally. No API keys, no external services, no ongoing costs.
License
MIT
Resources
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