# TradingView PineScript Backtest Engine

> Use this tool when you need to backtest and evaluate the performance of algorithmic trading strategies using PineScript code. It solves problems related to strategy optimization and risk assessment by providing detailed performance metrics, including returns, drawdowns, and trade statistics. The engine accepts PineScript strategy code as input and returns key performance indicators as output, making it ideal for traders and developers seeking to refine their trading approaches.

Canonical page: https://skillsregistry.net/skills/vtlk-tradingview-pinescript-backtest  
JSON: https://api.skillsregistry.net/v1/skills/vtlk-tradingview-pinescript-backtest

## Description

TradingView PineScript Backtest Engine provides MCP-compatible access to algorithmic trading strategy backtesting using TradingView's PineScript language. It accepts PineScript strategy code and returns performance metrics including returns, drawdowns, and trade statistics.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/vtlk-tradingview-pinescript-backtest)
- **Repository:** <https://github.com/vtlk/tv-pinescript-backtest-engine-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": "vtlk-tradingview-pinescript-backtest"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vtlk-tradingview-pinescript-backtest` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vtlk-tradingview-pinescript-backtest/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