# Use vid2context in LM Studio

LM Studio 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. Open the Program tab in the right sidebar, then Install, Edit mcp.json.

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

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

3. Print the config with this clone's paths, then add it to `mcp.json`. Merge it into `mcpServers` if the file already has other servers.

   ```sh
   printf '{"mcpServers":{"vid2context":{"command":"%s/node_modules/.bin/tsx","args":["%s/packages/mcp/src/bin.ts"]}}}\n' "$PWD" "$PWD"
   ```

## Check that it works

In a chat, the integrations menu lists vid2context. Pick a model that supports tool use.

## Try it

Ask LM Studio:

> 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:

```text
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](https://vid2context.com/docs/providers.md).

## Links

- [LM Studio MCP documentation](https://lmstudio.ai/docs/app/mcp)
- [YouTube transcript MCP server](https://vid2context.com/docs/how-to/youtube-transcript-mcp-server.md): what the tools do
- [Source on GitHub](https://github.com/nirholas/vid2context)