# Spark Optimizer

> Use this tool when you need to optimize Apache Spark code for better performance, as it analyzes PySpark code and applies enhancements to improve execution speed and efficiency. It solves problems of slow Spark job execution, inefficient resource management, and suboptimal query performance. The Spark Optimizer takes PySpark code as input and outputs optimized code with improved performance, making it ideal for data engineers seeking to streamline their Spark workflows.

Canonical page: https://skillsregistry.net/skills/vgiri2015-spark-optimizer  
JSON: https://api.skillsregistry.net/v1/skills/vgiri2015-spark-optimizer

## Description

AI-Spark-MCP-Server provides intelligent Apache Spark code optimization through Claude AI integration. It analyzes PySpark code and applies performance enhancements including query optimization, resource management improvements, and execution tuning - resulting in significant performance gains (up to 74% faster execution in examples). The server exposes tools for code optimization and performance analysis via the MCP protocol, making it valuable for data engineers looking to improve Spark job efficiency without manual code refactoring.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/vgiri2015-spark-optimizer)
- **Repository:** <https://github.com/vgiri2015/ai-spark-mcp-server>

## 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": "vgiri2015-spark-optimizer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vgiri2015-spark-optimizer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vgiri2015-spark-optimizer/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