Use vid2context in Goose#

Goose can read any video through the vid2context MCP server: the transcript with timestamps, the metadata and the chapters. No key is needed. Captions come straight from the platform, and when a video has none, speech-to-text falls back through free and keyless Whisper rungs.

Install#

These steps use a clone of the repo (the npm package is not published yet, so these steps run the server from source).

1. Clone the repo and install it once (Node.js 22 or newer). Run the next commands from the repo root.

   shCopy

   git clone https://github.com/nirholas/vid2context.git
   cd vid2context
   npm install

2. Print the start command with this clone's paths:

   shCopy

   echo "$PWD/node_modules/.bin/tsx" "$PWD/packages/mcp/src/bin.ts"

3. Run goose configure, choose Add Extension, then Command-line Extension, name it vid2context and paste that command.

Check that it works#

Start goose session and ask which extensions are enabled, or open Extensions in Goose Desktop.

Try it#

Ask Goose:

Get the transcript of https://www.youtube.com/watch?v=jNQXAC9IVRw and summarize it with timestamps.

The get_transcript tool hands the agent a short header and the timed transcript. This is the real text it returns for "Me at the zoo", rendered by vid2context from a recorded run:

Title: Me at the zoo
Channel: jawed
URL: https://www.youtube.com/watch?v=jNQXAC9IVRw
Duration: 0:19
Transcript: creator-captions, en (youtube-captions)
Chapters: 0:00 Intro | 0:05 The cool thing | 0:17 End

[0:01] All right, so here we are, in front of the elephants
[0:05] the cool thing about these guys is that they have really...
[0:07] really really long trunks
[0:12] and that's cool
[0:14] (baaaaaaaaaaahhh!!)
[0:16] and that's pretty much all there is to say

The agent can now cite moments by timestamp. For long videos it can call get_outline first and read only the sections it needs.

Optional keys#

Every key is optional. Each one unlocks more free rungs, which run before the keyless ones:

• GROQ_API_KEY: Groq free tier: fast Whisper speech-to-text and LLMs
• GEMINI_API_KEY: Google AI Studio free tier LLMs
• OPENAI_API_KEY: OpenAI, used last and only when set
• OLLAMA_BASE_URL: Local Ollama server, for example http://localhost:11434/v1
• LOCAL_STT_BASE_URL: Local OpenAI-compatible speech-to-text server, for example http://localhost:8000/v1

The full list, with every model override, is in Providers and rungs.

Links#

• Goose MCP documentation
• YouTube transcript MCP server: what the tools do
• Source on GitHub