MCP Server | Parrot Scribe Docs

What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI assistants interact with external tools and data sources through a structured interface. Parrot Scribe includes a built-in MCP server, so there is nothing extra to install.

How It Works

The MCP server runs inside Parrot Scribe as a single process. There is no separate server to manage.

Built-in: The server is part of Parrot Scribe itself - no external packages or dependencies required.
Unix domain socket: Communication uses a local Unix socket with owner-only access.
Shim bridge: The bundled parrotscribe-mcp-shim bridges stdio MCP hosts to the local socket.
Token authentication: Clients must present a valid token during handshake.
Off by default: The MCP listener is disabled until you explicitly enable it. When disabled, no MCP socket is exposed.

Enabling the MCP Server

Open Parrot Scribe.
Go to Settings > MCP.
Toggle Enable MCP Server.
In the Clients section, create a token for each MCP client you want to allow.
Copy the token immediately when shown. It is only shown once.

Configuring AI Hosts

Claude Desktop

Add to claude_desktop_config.json (typically at ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "parrotscribe": {
      "command": "/Applications/Parrot Scribe.app/Contents/MacOS/parrotscribe-mcp-shim",
      "args": ["--token", "<token-from-settings>"]
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "parrotscribe": {
      "command": "/Applications/Parrot Scribe.app/Contents/MacOS/parrotscribe-mcp-shim",
      "args": ["--token", "<token-from-settings>"]
    }
  }
}

Restart your AI host after saving.

See It In Action

This is a simulated run that showcases different scenarios where Parrot Scribe MCP can be useful. Each example is built from real functionality available after you enable the MCP server and connect a client such as OpenCode, Claude Code, or a similar extension with behavioral and role-specific instructions.

Access Model

Parrot Scribe applies controls at two layers:

Client access level (set per client in Settings):
- Disabled: No tool access.
- Enabled: Default when a token is created. Status and operational tools are allowed (unless a capability toggle is turned off); destructive tools always prompt.
- Trusted: Status, operational, and destructive tools are allowed without prompts.
Tool class:

Status tools - Always Allowed

No approval needed. Read-only status information.

Tool	Description
`get_status`	Recording state (active/idle)

Operational tools

Allowed for clients in Enabled or Trusted mode. Individual capabilities can be toggled per client.

Tool	Description
`list_sessions`	Session metadata and speaker names
`read_transcript`	TOON-formatted transcript content
`search_sessions`	Content search across recent sessions
`live_transcript`	Real-time feed during recording
`list_speakers`	Enrolled speakers with metadata
`identify_speakers`	Identify speakers in a session using provided names
`reassign_segment_speaker`	Reassign a specific transcript segment to an existing speaker
`start_recording`	Start transcription recording
`stop_recording`	Stop transcription recording

Destructive tools

For Enabled clients, every call prompts. Trusted clients can run these without prompts.

Tool	Description
`remove_speaker`	Delete voice model (reversible - can re-enroll later)
`forget_speaker`	Permanently remove a voice model and delete sessions containing that speaker
`delete_session`	Delete session and associated audio

Token Lifecycle

Issue one token per client from Settings > MCP in the Clients section.
Tokens are stored as hashed records at rest.
Revoking a token immediately removes that client access and disconnects active sessions for that token.

Security Model

Four layers protect your data:

Transport: Local Unix socket with owner-only access.
Authentication: Token is required at connection handshake.
Authorization: Per-client access levels, capability toggles, and destructive-operation prompts.
Rate controls: Per-client throttling and bulk-access safeguards reduce automated misuse.

Use Cases

Meeting monitor - AI follows a live call and surfaces relevant context
Action item tracker - AI detects commitments and prepares follow-up tasks
Session summarizer - AI generates structured summaries after recordings
Research assistant - AI searches historical transcripts for patterns

If you want the end-to-end workflow for Whisper-based local meeting notes on Mac, including import-later recordings and optional local-model setups, read Local Meeting Notes with Whisper.

Learn More

Model Context Protocol Documentation