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FixtureForge

timeweaver-mcp

by FixtureForge
README.md
# TimeWeaver MCP

**Synthetic time-series test data, on demand, inside your AI client.** Generate realistic series with configurable trend, seasonality, noise, anomalies, and multiple correlated streams — perfect for testing dashboards, charts, monitoring/alerting, forecasting models, and anomaly detection. Output as JSON, CSV, or SQL.

Part of the [fixturelab](https://github.com/FixtureForge) test-data tools. Its sibling [SeedWeaver](https://github.com/FixtureForge/seedweaver-mcp) does relational/database test data.

## Why

LLMs are unreliable at hand-generating coherent time-series — trends drift, "seasonality" doesn't actually repeat, and correlations between series are fake. TimeWeaver generates data with **verifiable statistical properties**: a linear trend really has the slope you asked for, a seasonal cycle really repeats at its period, two correlated series really hit the target correlation, and AR(1) noise really has the autocorrelation you set.

## Install

```
npx -y timeweaver-mcp
```

Add to your MCP client config (e.g. Claude Desktop `claude_desktop_config.json`):

```json
{
  "mcpServers": {
    "timeweaver": {
      "command": "npx",
      "args": ["-y", "timeweaver-mcp"]
    }
  }
}
```

To unlock Pro, add your license key:

```json
{
  "mcpServers": {
    "timeweaver": {
      "command": "npx",
      "args": ["-y", "timeweaver-mcp"],
      "env": { "TIMEWEAVER_LICENSE": "YOUR-KEY-HERE" }
    }
  }
}
```

## Tools

- **`generate_timeseries`** — generate data from a preset and/or explicit components (length, frequency, baseline, trend, seasonality, noise, anomalies, correlated series). Output JSON / CSV / SQL.
- **`list_presets`** — list built-in presets: `ecommerce_sales`, `server_cpu`, `iot_temperature`, `website_traffic`, `stock_price`, `api_latency_ms`.

## Examples

> "Generate 90 days of daily e-commerce sales using the ecommerce_sales preset."

> "Generate 3 correlated server CPU series over 500 minutes with correlation 0.8, as CSV."

> "Make an hourly temperature series with a daily cycle and a level shift on day 5, as SQL into a table called readings."

## Free vs Pro

| | Free | Pro |
|---|---|---|
| Points per series | 200 | up to 100,000 |
| Series | 1 | up to many, correlated |
| Trend | none / linear | + exponential, logistic |
| Seasonality | 1 cycle | multiple cycles |
| Noise | gaussian | + AR(1) autocorrelated |
| Anomalies | – | spikes, level shifts, trend changes, dropouts |
| Output | JSON | + CSV, SQL |
| Deterministic seed | – | ✓ |

Pro: **$19/mo** or **$39 one-time** → https://fixtureforge.gumroad.com/l/timeweaver

## License

MIT (the server code). Pro features require a valid license key.

TDQS

A4.2/5.0

Scored across 2 tools

Disambiguation5/5

The two tools are completely distinct: one lists predefined presets, the other generates actual time-series data. There is no overlap or ambiguity between them.

Naming Consistency5/5

Both tool names follow the consistent verb_noun pattern with snake_case: list_presets and generate_timeseries. The naming is predictable and clear.

Tool Count3/5

With only 2 tools, the server feels minimal for the described functionality (configurable trend, seasonality, noise, anomalies, multiple output formats). While focused, it could benefit from splitting generation into separate tools for configuration or output format selection.

Completeness4/5

The server covers the core use case of generating time-series data with presets, but lacks tools for creating or editing presets, which would be a natural extension. The missing capability is minor and agents can work around it by overriding parameters.

Maintenance

ActivityInactive
ResponsivenessNo issues