YouTube MCP Server

The yt‑mcp-server is a lightweight Model Context Protocol (MCP) server that bridges the gap between AI assistants and YouTube’s rich media ecosystem. By exposing a small set of focused tools, the server lets developers turn natural‑language requests into precise YouTube URLs and thumbnails without having to write custom parsing logic. This capability is especially valuable for chatbots or content‑generation assistants that need to fetch or embed videos on demand, ensuring that the assistant can reliably handle a variety of YouTube link formats and provide consistent results.

At its core, the server offers three intuitive tools. transforms a video ID into a fully‑qualified watch link, optionally inserting a start time to jump straight to a specific moment in the video. retrieves the direct URL for a video’s thumbnail, enabling visual previews or quick image references. Finally, accepts any common YouTube URL—short links, embed codes, or share URLs—and returns the canonical watch format along with the extracted video ID. These functions abstract away the idiosyncrasies of YouTube’s URL patterns, allowing AI clients to focus on higher‑level logic rather than string manipulation.

Developers can integrate the server into their AI workflows by simply adding it to the MCP client configuration. Once registered, an LLM can invoke these tools via standard tool calls, receiving structured responses that include the resolved URLs or IDs. This pattern is ideal for scenarios such as:

• Content recommendation – an assistant suggests relevant videos and automatically generates embed links.
• Automated video summaries – a tool fetches the thumbnail and watch URL for use in generated articles or newsletters.
• Educational chatbots – students ask for a specific clip, and the assistant returns a link that starts at the requested timestamp.

The server’s lightweight implementation in Python 3.12+ and its reliance on the UV package manager make deployment straightforward, whether running from a GitHub release or developing locally. Its unique advantage lies in the seamless normalization of diverse YouTube URLs, a common pain point for many AI applications. By handling these nuances behind the scenes, the yt‑mcp-server empowers developers to build richer, more reliable media interactions within their AI assistants.