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 "Deploy 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 Server analyze 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.
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.
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 |
Related MCP server: CRE Intelligence MCP
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.
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?"
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.
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
Environment Variable | Default | Description |
|
| Path to folder with |
npm run dev # Watch mode with tsx
npm run build # Compile TypeScript
npm start # Run compiled serverThis 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.
Zero. Runs entirely locally. No API keys, no external services, no ongoing costs.
MIT
Apply a McKinsey-style consulting framework to a business problem using real estate industry data.
This is Mikensey's signature tool. It doesn't just search transcripts — it THINKS like a consultant. Choose a framework, describe your situation, and get a structured strategic analysis backed by real industry evidence.
Available frameworks:
"2x2": 2×2 positioning matrix — plot options across two dimensions to reveal strategic positioning
"scr": Situation-Complication-Resolution — structure a recommendation as an irrefutable argument
"issue_tree": Issue Tree — decompose a complex problem into MECE sub-problems with testable hypotheses
"porters": Porter's Five Forces — analyze competitive dynamics and industry attractiveness
"value_chain": Value Chain Analysis — map where value is created and captured, find integration opportunities
"mece": MECE Breakdown — structure any analysis to be mutually exclusive and collectively exhaustive
Args:
framework (string): Which consulting framework to apply
situation (string): Describe your business context, challenge, or question
role (string): Your role — "agent", "broker", "mortgage_pro", or "founder"
custom_axes (string, optional): For 2×2 only — specify custom axes (e.g., "Growth Rate vs. Profitability")
Returns: A structured strategic analysis using the chosen framework, populated with real industry benchmarks, quotes from leaders, and specific recommendations.
Inputs: framework (required), situation (required), role (required), custom_axes.
Get a McKinsey-style strategy brief structured as Situation-Complication-Resolution (SCR), grounded in real industry data from 53 podcast episodes.
This is the executive-ready output tool. It generates a complete strategy memo using the SCR framework:
SITUATION: Undeniable facts about the current state (backed by benchmarks)
COMPLICATION: What has changed or is broken (backed by transcript evidence)
RESOLUTION: Specific recommendations with supporting data
For deeper analysis with specific frameworks (2×2, Issue Trees, Porter's, etc.), use mikensey_analyze instead.
Args:
role (string): Your role — "agent", "broker", "mortgage_pro", or "founder"
situation (string): Describe your business situation and challenge in detail
topic (string, optional): Focus area — "growth", "retention", "mortgage", "tech", "differentiation", "profitability"
Returns: An SCR-structured strategy brief with benchmarks, evidence, and specific recommendations.
Inputs: role (required), situation (required), topic.
Look up real estate, mortgage, and proptech industry benchmarks and metrics from podcast conversations.
Contains specific numbers cited by industry leaders: attach rates, origination costs, agent productivity, growth rates, conversion rates, and more.
Args:
query (string, optional): Filter benchmarks by keyword (e.g., "mortgage", "agent", "cost")
Returns: Benchmark data with metric name, value, context, and source.
Examples:
"attach rate" → mortgage attach rate benchmarks from Prosperity, industry averages
"cost" → origination costs, marketing costs, compliance costs
"agent" → agent counts, growth rates, retention metrics
No query → returns all benchmarks
Inputs: query.
Read the full or partial transcript of a specific podcast episode.
Use this to deep-dive into a specific conversation. Use mikensey_list_episodes or mikensey_search first to find the episode id.
Args:
episode_id (string): Episode slug (e.g., "justin-messer-hand-to-hand-combat-in-mortgage")
offset (number): Start reading from this line number (default: 0)
limit (number): Number of lines to return (default: 200)
Returns: Episode transcript text with metadata.
Inputs: episode_id (required), offset, limit.
Browse two categories of frameworks available in Mikensey:
Industry Frameworks — Mental models extracted from podcast conversations (e.g., 3-Lever Consumer Value Model, Brokerage Pretzel, Agent Value Equation, W-H-Y mortgage sales)
Consulting Frameworks — McKinsey-style analytical tools you can apply to any problem (2×2 Matrix, SCR, Issue Trees, Porter's Five Forces, Value Chain, MECE)
Args:
audience (string, optional): Filter industry frameworks by target audience — "agents", "mortgage", or "founders"
type (string, optional): Filter by framework type — "industry" (from podcasts) or "consulting" (McKinsey toolkit) or "all" (default)
Returns: Framework name, description, when to use, and examples.
To actually APPLY a consulting framework to your specific situation, use mikensey_analyze.
Inputs: audience, type.
List all available podcast episodes with guest names, dates, and topics.
Use this to browse what's available or find a specific episode.
Args:
filter (string, optional): Filter by guest name, topic, or keyword
limit (number): Max results (default: 20)
offset (number): Skip this many results for pagination (default: 0)
Returns: Episode list with id, guest, title, date, and word count.
Inputs: filter, limit, offset.
Search across all Mike DelPrete podcast transcripts for topics, quotes, metrics, or advice.
Use this tool to find what industry leaders have said about specific topics in real estate, mortgage, and proptech.
Args:
query (string): Search terms (e.g., "mortgage attach rate", "agent retention", "AI in real estate")
limit (number): Max results to return (default: 5, max: 10)
Returns: Matching transcript excerpts with episode info, guest name, and relevant quotes.
Examples:
"mortgage attach rate" → finds discussions about mortgage integration success rates
"agent equity ownership" → finds eXp and Real Brokerage discussions
"cost of origination" → finds Stratmore Group data on mortgage economics
Inputs: query (required), limit.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 7 tools
Each tool has a clearly distinct purpose with no overlap: mikensey_analyze applies frameworks, mikensey_get_advice generates SCR briefs, mikensey_get_benchmarks retrieves metrics, mikensey_get_episode fetches transcripts, mikensey_get_frameworks lists frameworks, mikensey_list_episodes shows episodes, and mikensey_search queries transcripts. The descriptions explicitly differentiate them, such as advising to use mikensey_analyze for specific frameworks versus mikensey_get_advice for SCR memos.
All tools follow a consistent snake_case naming pattern with the prefix 'mikensey_' and clear verb_noun combinations: analyze, get_advice, get_benchmarks, get_episode, get_frameworks, list_episodes, and search. This uniformity makes the tool set predictable and easy to navigate, with no deviations in style or convention.
With 7 tools, the server is well-scoped for its purpose of providing McKinsey-style consulting analysis on real estate industry data. Each tool serves a specific function—from analysis and advice to data retrieval and search—without redundancy, making the count ideal for covering the domain comprehensively without being overwhelming.
The tool set offers complete coverage for the domain, including analysis (mikensey_analyze), advice generation (mikensey_get_advice), data access (mikensey_get_benchmarks, mikensey_get_episode, mikensey_list_episodes), framework browsing (mikensey_get_frameworks), and search (mikensey_search). There are no obvious gaps; agents can perform end-to-end tasks from exploration to structured recommendations without dead ends.
AI-native real estate discovery with structured property search and market intelligence.
AI agent access to your Searcher OS deal feed, pipeline, buy boxes, CIM analysis, and broker CRM.
Research, strategy, financial models and decks, priced and approved per job, in your AI assistant
Podcast knowledge for AI agents: search episodes, pull transcripts and ask questions.
