# tslab-mcp

> tslab-mcp — pedrobtz-tslab-mcp. Use this tool when you need to perform accurate and reproducible time series forecasting, or detect anomalies in data, by leveraging Python statistical and foundation models. It solves problems related to data analysis and prediction by providing a range of tools, including data loading, cross-validation, and forecasting. The tool takes in time series data as input and outputs forecasted values and anomaly detection results, making it ideal for use cases where data-driven insights are crucial.

Canonical page: https://skillsregistry.net/skills/pedrobtz-tslab-mcp  
JSON: https://api.skillsregistry.net/v1/skills/pedrobtz-tslab-mcp

## Description

Enables users to perform deterministic time series forecasting through Claude by running reproducible Python statistical and foundation models, providing tools for loading data, cross-validation, forecasting, anomaly detection, and exporting re-runnable manifests without any LLM involvement.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/io9gtn0d75)
- **Repository:** <https://github.com/pedrobtz/tslab-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "pedrobtz-tslab-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pedrobtz-tslab-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pedrobtz-tslab-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt