# Okahu

> Use this tool when you need to manage and analyze genAI trace data to gain insights into AI workload performance, reliability, and cost. It provides a cloud-hosted server for instrumenting applications, capturing traces, and optimizing AI observability. Ideal for developers seeking to improve the efficiency and reliability of their AI applications.

Canonical page: https://skillsregistry.net/skills/okahu  
JSON: https://api.skillsregistry.net/v1/skills/okahu

## Description

Cloud-hosted MCP server for Okahu's AI observability platform. Provides tools to manage and analyze genAI trace data generated by the Monocle tracing framework. Enables developers to instrument applications, capture traces, and gain insights into AI workload performance, reliability, and cost.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/okahu)

## 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": "okahu"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/okahu` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/okahu/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