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zentala 转录分析服务器

一个为Transcripter项目提供人工智能功能的模型上下文协议服务器,包括搜索和总结转录内容的工具,以及访问转录和分析数据的资源。

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README

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

help

运行方式说明

cloud

托管运行

托管运行通常表示这个 MCP Server 由服务方环境承载,用户一般按页面提供的连接方式或授权流程接入,不需要在本地长期启动一个 MCP 进程

  1. 打开服务方连接页
  2. 完成授权或复制端点
  3. 在 MCP 客户端中连接
terminal

本地运行 / 其它方式

本地运行通常需要用户在自己的电脑或服务器上安装依赖,把 server_config 复制到 MCP 客户端,并按 env_schema 补齐环境变量、密钥或其它配置

  1. 复制 server_config
  2. 安装所需依赖
  3. 补齐环境变量后重启客户端