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# migas-mcp

MCP server for [Migas](https://migas.ai) meeting transcripts. Query your local meeting data from Claude Desktop, Claude Code, Cursor, or any MCP-compatible AI assistant.

## What it does

Migas transcribes your meetings locally on your Mac. This MCP server gives AI assistants read-only access to that data so you can ask questions like:

- "What did we discuss about the roadmap last week?"
- "What has Sarah said about the budget across all meetings?"
- "Show me the transcript from yesterday's standup"

## Tools

| Tool | Description |
|------|-------------|
| `list_meetings` | Recent meetings with title, date, duration, participants |
| `get_meeting_transcript` | Full speaker-labeled transcript for a meeting |
| `search_transcripts` | Full-text search across all meeting transcripts |
| `find_speakers` | Look up enrolled speakers by name |
| `get_speaker_contributions` | Everything a speaker said across all meetings |

## Install

### Claude Desktop

Add to `~/Library/Application Support/Claude/claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "migas": {
      "command": "npx",
      "args": ["-y", "migas-mcp"]
    }
  }
}
```

### Claude Code

```bash
claude mcp add migas -- npx -y migas-mcp
```

### Cursor

Add to MCP settings:

```json
{
  "mcpServers": {
    "migas": {
      "command": "npx",
      "args": ["-y", "migas-mcp"]
    }
  }
}
```

## Requirements

- [Migas](https://migas.ai) installed and launched at least once (creates the local database)
- macOS (reads from `~/Library/Application Support/Migas/meetings.db`)

## Privacy

The MCP server is **read-only** and connects to your **local** Migas database. No meeting data is sent anywhere by the server itself. When you ask an AI assistant a question, only the relevant transcript text is sent to the AI provider, same as using Migas's built-in chat.

## Development

```bash
bun install
bun test
bun run build
```

TDQS

A4.2/5.0

Scored across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: listing meetings, retrieving a transcript, searching transcripts, finding speakers, and aggregating speaker contributions. There is no functional overlap or ambiguity between tools.

Naming Consistency5/5

All tool names follow the same verb_noun pattern in snake_case (e.g., list_meetings, get_meeting_transcript, search_transcripts), which makes the naming scheme predictable and consistent across the entire set.

Tool Count5/5

Five tools is a well-scoped count for a meeting transcription and speaker analytics server. Each tool covers a distinct functional area without redundancy or excessive granularity.

Completeness5/5

The server provides complete coverage of its core domain: browsing meetings, reading transcripts, full-text search, and per-speaker contribution analysis. There are no obvious gaps or dead ends in the workflow.

Maintenance

ActivityInactive
ResponsivenessNo issues