# speaker-context-layer

> speaker-context-layer — sammyghe-speaker-context-layer. Use this tool when you need to identify and attribute speakers in a private setting, such as a room or transcript, without relying on cloud services. It solves the problem of speaker recognition and attribution in local environments, providing per-language voiceprints and calibrated match thresholds for accurate identification. The speaker-context-layer tool takes in audio or transcript inputs and outputs identified speaker information, making it ideal for use cases requiring private and consent-based speaker identification.

Canonical page: https://skillsregistry.net/skills/sammyghe-speaker-context-layer  
JSON: https://api.skillsregistry.net/v1/skills/sammyghe-speaker-context-layer

## Description

Local MCP server for private, consent-based speaker identification and attribution, with per-language voiceprints and calibrated match thresholds. It lets AI assistants know who is speaking in a room or transcript without cloud services.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/dhu69vb6r5)
- **Repository:** <https://github.com/sammyghe/speaker-context-layer>

## 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": "sammyghe-speaker-context-layer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sammyghe-speaker-context-layer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sammyghe-speaker-context-layer/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