# omega-stenographer-mcp

> Use this tool when you need to capture and summarize complex conversations, extract key decisions and blockers, and generate searchable notes. Omega Stenographer MCP ingests conversation turns, analyzes agent reasoning, and produces live running notes and compressed briefs. Ideal for use in multi-agent ecosystems, such as the Omega Universe, where passive observation and knowledge retention are crucial.

Canonical page: https://skillsregistry.net/skills/vrtxomega-omega-stenographer-mcp  
JSON: https://api.skillsregistry.net/v1/skills/vrtxomega-omega-stenographer-mcp

## Description

Omega Stenographer MCP is the passive observation layer of the VERITAS & Sovereign Ecosystem (Omega Universe). Where Omega Brain enforces governance and VERITAS gates evaluate artifact integrity, Stenographer observes: it ingests every conversation turn, extracts decisions and blockers from agent reasoning, builds live running notes, and compresses stale context into searchable briefs before it ca

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/so2qqzlg25)
- **Repository:** <https://github.com/VrtxOmega/omega-stenographer-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": "vrtxomega-omega-stenographer-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vrtxomega-omega-stenographer-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vrtxomega-omega-stenographer-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