Echomindr

3,500+ real founder moments from 60+ podcasts — searchable by AI agents.

Each moment: a named founder, a verbatim quote, a decision taken, an outcome observed, a lesson extracted — with a timestamped link to the source. Not summaries. Not paraphrases. What actually happened.

Why

AI agents give generic startup advice. Echomindr gives them access to what founders actually did.

Ask: "How did founders handle their first pricing?" Get: Kevin Hale's 10-5-20 rule, Josh Pigford charging $249/month from day one, Madhavan Ramanujam's options trick — with quotes, outcomes, and source links.

Ask: "What did founders do when they nearly ran out of money?" Get: Airbnb selling cereal boxes, Notion's near-collapse during COVID, Calm's years of slow growth before the breakout — directly from the founders who lived it.

Quick start

API (REST)

# Search for founder experiences
curl "https://echomindr.com/search?q=pricing&limit=5"

# Describe a situation, get matching experiences (vector search)
curl -X POST "https://echomindr.com/situation" \
  -H "Content-Type: application/json" \
  -d '{"situation": "B2B SaaS founder with free pilots that won'\''t convert to paid"}'

# Get moment details
curl "https://echomindr.com/moments/{id}"

# Find similar moments
curl "https://echomindr.com/similar/{id}?limit=5"

API docs: echomindr.com/docs

MCP (for AI agents)

Connect via remote MCP: https://echomindr.com/mcp/

Or add to Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "echomindr": {
      "command": "python",
      "args": ["echomindr_mcp.py"],
      "env": {
        "ECHOMINDR_API_URL": "https://echomindr.com"
      }
    }
  }
}

3 MCP tools:

• search_experience — semantic search for founder stories by situation
• get_experience_detail — full details of a moment (quote, decision, outcome, lesson)
• find_similar_experiences — related founder stories by shared themes

llms.txt

https://echomindr.com/llms.txt

Data

• 3,500+ moments from 340+ podcast episodes across 60+ shows
• 52 canonical situations across 10 thematic families (PMF, growth, pricing, fundraising, team, operations, resilience, strategy, founder psychology, hostile environments)
• 5 moment types: decision, problem, lesson, signal, advice
• 5 stages: idea, mvp, traction, scale, mature
• Sources: How I Built This, Lenny's Podcast, 20 Minute VC, Acquired, Y Combinator, My First Million, GDIY (Génération Do It Yourself), Disrupting Japan, Silicon Carne, Startup Ministerio, Kevin Kamis, Wall Street Paper, Valy Sy (China), Matt & Ari (Canada), Oscar Lindhardt (Denmark), Aidan Walsh (USA)

Each moment: summary · verbatim quote · decision · outcome · lesson · stage · tags · timestamp link

Self-hosting

To run your own instance with the sample data:

git clone https://github.com/echomindr/echomindr.git
cd echomindr
pip install -r requirements.txt

# Build a sample database
python echomindr_build_db.py --sample

# Start the API
python echomindr_api.py
# → http://localhost:8000/docs

To build the full database, you need your own podcast transcriptions and Claude API key. See echomindr_extract_v2.py for the extraction pipeline.

Architecture

Podcast audio → Deepgram (transcription) → Claude (extraction) → SQLite → FastAPI → MCP

The extraction pipeline turns long-form podcast interviews into structured, searchable moments. Each episode yields 8–15 moments on average. Semantic search uses BAAI/BGE-M3 embeddings (1024-dim) via sqlite-vec.

Endpoints

Endpoint	Method	Description
/search	GET	Full-text search with stage/type filters
/situation	POST	Describe a situation, get matching experiences (vector search)
/moments/{id}	GET	Full moment detail
/similar/{id}	GET	Similar moments by shared tags
/taxonomy	GET	52 canonical situations across 10 families
/stats	GET	Database statistics
/llms.txt	GET	LLM-optimized API description
/docs	GET	Swagger documentation

License

MIT — the code is open source. The hosted database at echomindr.com is a managed service.

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Built by Thierry — author of "The System That Learns Wins" and "Designing for Permanent Hostility".