Initial commit: Lean Experiment MCP server v1.0.0

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Scott Scoble 2026-05-02 11:30:27 -07:00
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# Lean Experiment MCP Server
A Model Context Protocol (MCP) server for running Lean Startup experiments. Define hypotheses, track observations, and make data-driven decisions — all from within your agent workflow.
## Why This Exists
Agents need to validate ideas before building. This MCP server gives agents the same Lean Startup tooling that human startups use: hypothesis definition, metric tracking, and explicit persevere/pivot/kill decisions.
## Tools
### `define_experiment`
Create a new experiment with hypothesis, success criteria, and kill criteria.
```json
{
"name": "MCP Server Adoption Test",
"hypothesis": "If I publish a free MCP server, 50+ agents will install it in 30 days because the registry has 180k users",
"success_criteria": "50+ stars/downloads in 30 days, 5+ issues opened",
"kill_criteria": "Zero engagement after 14 days",
"duration_days": 30
}
```
### `record_observation`
Log a data point for an active experiment.
```json
{
"experiment_id": "exp_...",
"metric": "github_stars",
"value": 12,
"notes": "Posted on HN, got 3 upvotes"
}
```
### `get_experiment_status`
Get full status with metrics summary, days remaining, and observations.
### `list_experiments`
List all experiments with status, day count, and observation count.
### `make_decision`
Make a decision: **persevere**, **pivot**, or **kill**.
```json
{
"experiment_id": "exp_...",
"decision": "kill",
"reason": "Zero installs after 14 days. Hypothesis invalidated."
}
```
### `update_experiment`
Update notes or extend duration.
## Installation
### Via npx (no install)
```json
{
"mcpServers": {
"lean-experiments": {
"command": "npx",
"args": ["lean-experiment-mcp"]
}
}
}
```
### Via npm
```bash
npm install -g lean-experiment-mcp
```
## Data Storage
All experiments stored in `~/.lean-experiments/experiments.db` (SQLite).
## Example Workflow
1. **Define:** `define_experiment` with hypothesis and success/kill criteria
2. **Ship:** Build the thing, publish it
3. **Record:** Every few days, log metrics with `record_observation`
4. **Decide:** At the end, use `make_decision` to persevere, pivot, or kill
5. **Learn:** Review all experiments with `list_experiments`
## License
MIT