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# ⭐⭐ mcp-webcam 0.2.0 - the 50 Star Update ⭐⭐
In celebration of getting 52 GitHub stars, `mcp-webcam 0.2.0` is here! Now supports streamable-http!! No installation required! - try it now at [`https://evalstate-mcp-webcam.hf.space/`](https://evalstate-mcp-webcam.hf.space/). You can specify your own UserID by adding `?user=<YOUR_USER_ID>` after the URL. Note this shared instance is for fun, not security - see below for instructions how to run your own copy locally.
In streamable-http mode multiple clients can connect simultaneously, and you can choose which is used for Sampling.
If we get to 100 stars I'll add another feature 😊.
## Multi-user Mode
When run in Streaming mode, if you set an MCP_HOST environment variable the host name is used as a prefix in URL construction, and 5 character UserIDs are automatically generated when the User lands on the webpage.
## mcp-webcam
MCP Server that provides access to your WebCam. Provides `capture` and `screenshot` tools to take an image from the Webcam, or take a screenshot. The current image is also available as a Resource.
### MCP Sampling
`mcp-webcam` supports "sampling"! Press the "Sample" button to send a sampling request to the Client along with your entered message.
> [!TIP]
> Claude Desktop does not currently support Sampling. If you want a Client that can handle multi-modal sampling request, try https://github.com/evalstate/fast-agent/ or VSCode (more details below).
## Installation and Running
### NPX
Install a recent version of [NodeJS](https://nodejs.org/en/download) for your platform. The NPM package is `@llmindset/mcp-webcam`.
To start in **STDIO** mode: `npx @llmindset/mcp-webcam`. This starts the `mcp-webcam` UI on port 3333. Point your browser at `http://localhost:3333` to get started.
To change the port: `npx @llmindset/mcp-webcam 9999`. This starts `mcp-webcam` the UI on port 9999.
For **Streaming HTTP** mode: `npx @llmindset/mcp-webcam --streaming`. This will make the UI available at `http://localhost:3333` and the MCP Server available at `http://localhost:3333/mcp`.
### Docker
You can run `mcp-webcam` using Docker. By default, it starts in **streaming mode**:
```bash
docker run -p 3333:3333 ghcr.io/evalstate/mcp-webcam:latest
```
#### Environment Variables
- `MCP_TRANSPORT_MODE` - Set to `stdio` for STDIO mode, defaults to `streaming`
- `PORT` - The port to run on (default: `3333`)
- `BIND_HOST` - Network interface to bind the server to (default: `localhost`)
- `MCP_HOST` - Public-facing URL for user instructions and MCP client connections (default: `http://localhost:3333`)
#### Examples
```bash
# STDIO mode
docker run -p 3333:3333 -e MCP_TRANSPORT_MODE=stdio ghcr.io/evalstate/mcp-webcam:latest
# Custom port
docker run -p 8080:8080 -e PORT=8080 ghcr.io/evalstate/mcp-webcam:latest
# For cloud deployments with custom domain (e.g., Hugging Face Spaces)
docker run -p 3333:3333 -e MCP_HOST=https://evalstate-mcp-webcam.hf.space ghcr.io/evalstate/mcp-webcam:latest
# Complete cloud deployment example
docker run -p 3333:3333 -e MCP_HOST=https://your-domain.com ghcr.io/evalstate/mcp-webcam:latest
```
## Clients
If you want a Client that supports sampling try:
### fast-agent
Start the `mcp-webcam` in streaming mode, install [`uv`](https://docs.astral.sh/uv/) and connect with:
`uvx fast-agent-mcp go --url http://localhost:3333/mcp`
`fast-agent` currently uses Haiku as its default model, so set an `ANTHROPIC_API_KEY`. If you want to use a different model, you can add `--model` on the command line. More instructions for installation and configuration are available here: https://fast-agent.ai/models/.
To start the server in STDIO mode, add the following to your `fastagent.config.yaml`
```yaml
webcam_local:
command: "npx"
args: ["@llmindset/mcp-webcam"]
```
### VSCode
VSCode versions 1.101.0 and above support MCP Sampling. Simply start `mcp-webcam` in streaming mode, and add `http://localhost:3333/mcp` as an MCP Server to get started.
### Claude Desktop
Claude Desktop does **NOT** support Sampling. To run `mcp-webcam` from Claude Desktop, add the following to the `mcpServers` section of your `claude_desktop_config.json` file:
```json
"webcam": {
"command": "npx",
"args": [
"-y",
"@llmindset/mcp-webcam"
]
}
```
Start Claude Desktop, and connect to `http://localhost:3333`. You can then ask Claude to `get the latest picture from my webcam`, or `Claude, take a look at what I'm holding` or `what colour top am i wearing?`. You can "freeze" the current image and that will be returned to Claude rather than a live capture.
You can ask for Screenshots - navigate to the browser so that you can guide the capture area when the request comes in. Screenshots are automatically resized to be manageable for Claude (useful if you have a 4K Screen). The button is there to allow testing of your platform specific Screenshot UX - it doesn't do anything other than prepare you for a Claude intiated request. NB this does not **not** work on Safari as it requires human initiation.
## Other notes
That's it really.
This MCP Server was built to demonstrate exposing a User Interface on an MCP Server, and serving live resources back to Claude Desktop.
This project might prove useful if you want to build a local, interactive MCP Server.
Thanks to https://github.com/tadasant for help with testing and setup.
Please read the article at [https://llmindset.co.uk/posts/2025/01/resouce-handling-mcp](https://llmindset.co.uk/posts/2025/01/mcp-files-resources-part1/) for more details about handling files and resources in LLM / MCP Chat Applications, and why you might want to do this.
