# ndjson-local-log-triage-mcp

> ndjson-local-log-triage-mcp — vola-trebla-ndjson-local-log-triage-mcp. Use this tool when you need to efficiently parse and analyze large NDJSON log files without excessive memory usage. It solves problems such as error detection and log filtering by providing features like pattern filtering, Z-score analysis for error spike detection, and severity timeline summarization. The tool takes NDJSON log files as input and outputs filtered and summarized log data, making it ideal for log triage and error analysis in resource-constrained environments.

Canonical page: https://skillsregistry.net/skills/vola-trebla-ndjson-local-log-triage-mcp  
JSON: https://api.skillsregistry.net/v1/skills/vola-trebla-ndjson-local-log-triage-mcp

## Description

MCP server that stream-parses NDJSON log files without loading them into memory — filter by pattern, detect error spikes via Z-score analysis, summarize severity timelines by time window.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/axw87m81pl)
- **Repository:** <https://github.com/vola-trebla/ndjson-local-log-triage-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": "vola-trebla-ndjson-local-log-triage-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vola-trebla-ndjson-local-log-triage-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vola-trebla-ndjson-local-log-triage-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