# inferwatch-mcp

> inferwatch-mcp — floatsmyboat-inferwatch. Use this tool when you need to monitor and analyze performance metrics of local AI instances, such as Ollama and vLLM, to optimize their operation and troubleshoot issues. It provides real-time and historical data on request rates, latency, and resource utilization through a stdio interface. This enables agents to make data-driven decisions and improve the efficiency of their AI workflows.

Canonical page: https://skillsregistry.net/skills/floatsmyboat-inferwatch  
JSON: https://api.skillsregistry.net/v1/skills/floatsmyboat-inferwatch

## Description

Enables agents to query real-time and historical metrics for locally served Ollama and vLLM instances, including request rates, latency, token counts, and GPU utilization, over stdio.

## Trust

- **Trust score (0–1):** 0.15
- **Verification tier:** scanned
- **Last scanned:** 2026-09-04

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-04

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/x7u76x17fq)
- **Repository:** <https://github.com/floatsmyboat/inferwatch>

## 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": "floatsmyboat-inferwatch"
    }
  }
}
```

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