# mcp-context-monitor

> Use this tool when you need to optimize AI coding agent performance by estimating context window usage via MCP, solving problems of state loss during compaction and enabling proactive preservation. It takes in context window data as input and outputs usage estimates, allowing for informed decisions on state management. This tool is ideal for use cases where AI agents require efficient memory management to maintain productivity.

Canonical page: https://skillsregistry.net/skills/sophia-labs-mcp-context-monitor  
JSON: https://api.skillsregistry.net/v1/skills/sophia-labs-mcp-context-monitor

## Description

Context window usage estimation for AI coding agents via MCP, enabling proactive state preservation before compaction.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fqjn18gejv)
- **Repository:** <https://github.com/sophia-labs/mcp-context-monitor>

## 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": "sophia-labs-mcp-context-monitor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sophia-labs-mcp-context-monitor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sophia-labs-mcp-context-monitor/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