# spark-sense-ai

> spark-sense-ai — sun7singh-spark-sense-ai. Use this tool when you need to diagnose and optimize Apache Spark job performance, as it analyzes stack traces and leverages large language models to identify failures and improve efficiency, supporting both EMR and local sources. It takes in Spark job logs and outputs actionable insights for optimization. Ideal for use cases where Spark job failures or performance issues need to be quickly identified and resolved.

Canonical page: https://skillsregistry.net/skills/sun7singh-spark-sense-ai  
JSON: https://api.skillsregistry.net/v1/skills/sun7singh-spark-sense-ai

## Description

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wwpbve421b)
- **Repository:** <https://github.com/sun7singh/spark-sense-ai>

## 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": "sun7singh-spark-sense-ai"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sun7singh-spark-sense-ai` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sun7singh-spark-sense-ai/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