mcp-server-youtube-transcript is an MCP (Model Context Protocol) server designed to allow users to directly download transcripts of YouTube videos. It supports multiple video URL formats, language-specific transcript retrieval, and provides detailed metadata in responses.
This tool is useful for extracting YouTube video transcripts with ease, supporting various video URL formats and enabling language-specific downloads. It integrates seamlessly with applications like Claude Desktop and offers robust error handling for common issues such as invalid URLs or unavailable transcripts.
The server was developed by kimtaeyoon83, as indicated by the GitHub repository path: kimtaeyoon83/mcp-server-youtube-transcript.
It can be installed via tools like Smithery or mcp-get and is compatible with applications like Claude Desktop. The server requires Node.js 18 or higher and npm/yarn for setup and usage.
The exact date isn't provided, but recent commit messages include updates like 'feat: Add YouTube transcript server' and 'chore: fix typo,' indicating active development.
You can install it using Smithery with the command: `npx @smithery/cli install @kimtaeyoon83/mcp-server-youtube-transcript --client claude`, or via mcp-get with `npx @michaellatman/mcp-get@latest install @kimtaeyoon83/mcp-server-youtube-transcript`.
You need Node.js 18 or higher, along with npm or yarn, to set up and run the server.
Yes, debugging is supported using the MCP Inspector tool, which can be launched with the command `npm run inspector`.
The 'get_transcript' tool accepts two inputs: `url` (a YouTube video URL or ID, required) and `lang` (language code for the transcript, optional, default is 'en').
The server handles errors such as invalid video URLs/IDs, unavailable transcripts, language availability issues, and network errors. It also validates all input parameters and implements timeouts for transcript retrieval.
Yes, mcp-server-youtube-transcript is licensed under the MIT License. Details can be found in the LICENSE file.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
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