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- Krillinai-MCP
Krillinai Mcp
What is Krillinai Mcp
Krillinai-MCP is a connector server based on the Model Context Protocol (MCP) that facilitates interaction between large language models (LLMs) and KrillinAI services. It acts as a bridge, enabling LLMs to utilize features such as subtitle generation, translation, and text-to-speech (TTS) provided by KrillinAI.
Use cases
Use cases for Krillinai-MCP include generating subtitles for online courses, translating video content for international audiences, creating bilingual subtitles for language learning, and enhancing video accessibility for hearing-impaired viewers.
How to use
To use Krillinai-MCP, first clone the repository and install the dependencies using pip or uv. Start the server by running the command ‘python krillinai-server.py’. Integrate it with an MCP client like Claude Desktop by editing its configuration file to include the server details.
Key features
Key features of Krillinai-MCP include file upload for video or audio, automatic subtitle generation, multilingual subtitle translation, bilingual subtitle support, TTS for subtitles with voice cloning, embedding subtitles into videos, and filtering of filler words to enhance subtitle quality.
Where to use
Krillinai-MCP can be used in various fields such as media production, educational content creation, accessibility services, and any application that requires subtitle generation and translation for video or audio content.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Krillinai Mcp
Krillinai-MCP is a connector server based on the Model Context Protocol (MCP) that facilitates interaction between large language models (LLMs) and KrillinAI services. It acts as a bridge, enabling LLMs to utilize features such as subtitle generation, translation, and text-to-speech (TTS) provided by KrillinAI.
Use cases
Use cases for Krillinai-MCP include generating subtitles for online courses, translating video content for international audiences, creating bilingual subtitles for language learning, and enhancing video accessibility for hearing-impaired viewers.
How to use
To use Krillinai-MCP, first clone the repository and install the dependencies using pip or uv. Start the server by running the command ‘python krillinai-server.py’. Integrate it with an MCP client like Claude Desktop by editing its configuration file to include the server details.
Key features
Key features of Krillinai-MCP include file upload for video or audio, automatic subtitle generation, multilingual subtitle translation, bilingual subtitle support, TTS for subtitles with voice cloning, embedding subtitles into videos, and filtering of filler words to enhance subtitle quality.
Where to use
Krillinai-MCP can be used in various fields such as media production, educational content creation, accessibility services, and any application that requires subtitle generation and translation for video or audio content.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Krillinai MCP 服务器
KrillinAI MCP 服务器是一个基于 Model Context Protocol (MCP) 的连接器,用于与 KrillinAI 服务进行交互。该服务器充当大语言模型 (LLM) 与 KrillinAI 服务之间的桥梁,使 LLM 能够使用 KrillinAI 的字幕生成、翻译、TTS 等功能。
功能特点
- 文件上传: 上传视频或音频文件到 KrillinAI 服务
- 字幕处理: 为视频自动生成字幕
- 翻译功能: 支持字幕翻译为多种语言
- 双语字幕: 生成双语字幕,支持自定义翻译字幕位置
- 文本转语音(TTS): 为字幕生成语音,支持音色克隆
- 字幕嵌入: 将字幕直接嵌入到视频中
- 语气词过滤: 过滤语气词,提高字幕质量
安装要求
- Python 3.12 或更高版本
- KrillinAI 服务(默认运行在 http://127.0.0.1:8888)
安装
# 克隆仓库
git clone https://github.com/yourusername/krillinai-mcp-server.git
cd krillinai-mcp-server
# 使用 pip 安装依赖
pip install -e .
# 或者使用 uv 安装(推荐)
uv pip install -e .
使用方法
启动服务器
python krillinai-server.py
与 MCP 客户端集成
Claude Desktop 示例配置
要将此服务器集成到 Claude Desktop,您需要编辑其 MCP 服务器配置文件。 在 macOS 上,该文件通常位于~/Library/Application Support/Claude/claude_desktop_config.json
。
{
"mcpServers": {
"krillinai-mcp-server": {
"isActive": true,
"name": "KrillinaiConnector",
"type": "stdio",
"description": "Connects to Krillinai for subtitle and media processing.",
"command": "/abs/path/to/your/project/.venv/bin/python",
"args": [
"/abs/path/to/your/project/krillinai-server.py"
],
"env": {}
}
}
}
请务必将 /abs/path/to/your/project/
替换为您的实际项目路径。
命令行选项
--krillinai-url
: 指定 KrillinAI 服务的 URL (默认: http://127.0.0.1:8888)--mcp-transport
: 指定 MCP 传输类型,可选 “stdio”(默认) 或 “streamable-http”--mcp-host
: 指定 HTTP 服务器主机(仅当 mcp-transport 为 “streamable-http” 时有效)--mcp-port
: 指定 HTTP 服务器端口(仅当 mcp-transport 为 “streamable-http” 时有效)
示例:
# 使用环境变量设置 KrillinAI URL
export KRILLINAI_URL="http://192.168.1.100:8888"
python krillinai-server.py
# 或者直接通过命令行参数设置
python krillinai-server.py --krillinai-url="http://192.168.1.100:8888"
# 使用 HTTP 传输并指定端口
python krillinai-server.py --mcp-transport="streamable-http" --mcp-port=8001
MCP 工具
该服务器提供了以下 MCP 工具供 LLM 使用:
-
配置管理工具
get_krillinai_configuration
: 获取当前 KrillinAI 连接配置set_krillinai_base_url
: 设置 KrillinAI 服务的 BASE URL
-
文件处理工具
upload_file_to_krillinai
: 将服务器可访问的文件上传到 KrillinAI
-
字幕处理工具
start_krillinai_subtitle_task
: 启动字幕处理任务get_krillinai_subtitle_task_details
: 获取字幕任务详情
-
内容获取工具
fetch_krillinai_file_as_text
: 获取 KrillinAI 文件的文本内容
工作流程示例
- 上传视频文件
- 启动字幕处理任务(可设置语言、翻译等参数)
- 查询任务状态直至完成
- 获取生成的字幕文件、语音或嵌入字幕的视频
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.