Server data from the Official MCP Registry
Synthetic time-series test data with trend, seasonality, noise, and anomalies, for any MCP client.
Synthetic time-series test data with trend, seasonality, noise, and anomalies, for any MCP client.
Valid MCP server (3 strong, 6 medium validity signals). 2 known CVEs in dependencies (0 critical, 2 high severity) Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
6 files analyzed · 3 issues found
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-fixtureforge-timeweaver-mcp": {
"args": [
"-y",
"timeweaver-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
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 test-data tools. Its sibling SeedWeaver does relational/database test data.
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.
npx -y timeweaver-mcp
Add to your MCP client config (e.g. Claude Desktop claude_desktop_config.json):
{
"mcpServers": {
"timeweaver": {
"command": "npx",
"args": ["-y", "timeweaver-mcp"]
}
}
}
To unlock Pro, add your license key:
{
"mcpServers": {
"timeweaver": {
"command": "npx",
"args": ["-y", "timeweaver-mcp"],
"env": { "TIMEWEAVER_LICENSE": "YOUR-KEY-HERE" }
}
}
}
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."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 | 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
MIT (the server code). Pro features require a valid license key.
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