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Transcripter MCP Server

Transcripter MCP Server

Public
zentala/zntl-mcp-server

Model Context Protocol server offering AI-powered transcription search, summarization, and analysis tools with standardized resource access for seamless integration and enhanced transcription workflows.

typescript
0 tools
May 30, 2025
Updated Jun 4, 2025

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MCP Server for Transcripter

A Model Context Protocol (MCP) server implementation for the Transcripter project. This package provides tools and resources for AI-powered features using the MCP standard.

Features

Tools

  • test-api: Test API endpoints and return the results
  • transcription-search: Search transcriptions with filtering and pagination
  • transcription-summary: Generate a summary of a transcription using AI

Resources

  • transcription://{id}: Access transcription data by ID
  • analysis://{id}: Access analysis data by ID

Requirements

  • Node.js >= 18.0.0
  • npm >= 7.0.0

Installation

npm install

Building

# Build for both ESM and CommonJS npm run build # Build for ESM only npm run build:esm # Build for CommonJS only npm run build:cjs

Running

# Start the MCP server on the default port (3500) npm run server # Start the MCP server on a custom port npm run server 4000

Testing

npm test

Usage Examples

Using the test-api tool

import { Client } from "@modelcontextprotocol/sdk/client"; import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse"; async function testApiEndpoint() { // Connect to the MCP server const transport = new SSEClientTransport("http://localhost:3500/sse", "http://localhost:3500/message"); const client = new Client(); await client.connect(transport); // Use the test-api tool const result = await client.tools.execute("test-api", { endpoint: "transcriptions", method: "GET", }); console.log(result); }

Using the transcription resource

import { Client } from "@modelcontextprotocol/sdk/client"; import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse"; async function getTranscription(id: number) { // Connect to the MCP server const transport = new SSEClientTransport("http://localhost:3500/sse", "http://localhost:3500/message"); const client = new Client(); await client.connect(transport); // Access the transcription resource const transcription = await client.resources.get(`transcription://${id}`); console.log(transcription); }

Integration with Transcripter

This MCP server integrates with the Transcripter project to provide AI-powered features for transcriptions and analyses. It serves as a standardized interface for AI model interactions.

Project Structure

  • src/cli.ts: Command-line interface for starting the MCP server
  • src/tools/: Implementation of MCP tools
  • src/resources/: Implementation of MCP resource providers
  • src/tests/: Tests for tools and resources

License

MIT

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