Integrations/MCP Server
MCP Server
Use ParrotScribe with AI assistants
What is MCP?
The Model Context Protocol (MCP) allows AI assistants like Claude to interact with external tools and services. The ParrotScribe MCP server enables AI agents to monitor transcriptions and access transcript data.
Use Cases
- Meeting Monitor: AI monitors a live call and surfaces relevant information
- Action Item Tracker: AI detects commitments and prepares follow-up actions
- Real-time Researcher: AI looks up technical terms mentioned in conversation
- Session Summarizer: AI generates structured summaries after calls
Prerequisites
- ParrotScribe installed with the
pscribeCLI in your PATH - Node.js 18 or higher
Installation
Option 1: NPX (Recommended)
No installation needed. Configure your AI agent to run:
npx @johanthoren/parrotscribe-mcp-server
Option 2: Global Install
npm install -g @johanthoren/parrotscribe-mcp-server
Configuration
Claude Desktop
Add to your claude_desktop_config.json (typically at ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"parrotscribe": {
"command": "npx",
"args": ["@johanthoren/parrotscribe-mcp-server"]
}
}
}
Claude Code
Add to your project's .mcp.json or global MCP config:
{
"mcpServers": {
"parrotscribe": {
"command": "npx",
"args": ["@johanthoren/parrotscribe-mcp-server"]
}
}
}
OpenCode
Add to the mcp section in ~/.config/opencode/opencode.jsonc:
{
"mcp": {
"parrotscribe": {
"type": "local",
"command": ["npx", "@johanthoren/parrotscribe-mcp-server"]
}
}
}
Restart your AI agent after saving the configuration.
Available Tools
| Tool | Description |
|---|---|
pscribe_start | Start real-time audio transcription |
pscribe_stop | Stop/pause the current transcription |
pscribe_status | Get service status, session ID, duration |
pscribe_tail | Get recent transcript entries with filtering |
pscribe_sessions | List past transcription sessions |
pscribe_new | Force start a new session |
pscribe_cat | Display complete sessions with time-based filtering |
pscribe_grep | Search for patterns across transcript sessions |