Synthetic time-series test data with trend, seasonality, noise, and anomalies, for any MCP client.
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.
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
npx -y timeweaver-mcpMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-fixtureforge-timeweaver-mcp": {
"command": "npx",
"args": [
"-y",
"timeweaver-mcp"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referencetimeweaver-mcpnpmio.github.FixtureForge/timeweaver-mcp works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.