# 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