MCP Webcam Server
# ⭐⭐ 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://webcam.fast-agent.ai/`](https://webcam.fast-agent.ai/). 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.
TDQS
Scored across 2 tools
The tools have overlapping purposes—both capture visual data from the user's environment—with 'capture' targeting the webcam and 'screenshot' targeting the screen, but descriptions could lead to confusion as 'capture' mentions examining objects the human shows, which might overlap with screen content. The boundaries are somewhat unclear, especially for agents interpreting use cases.
Tool names follow a consistent verb-based pattern ('capture' and 'screenshot'), both being single words describing the action. There are no deviations in style or casing, making them readable and predictable, though 'screenshot' is more specific than 'capture' in terms of naming convention.
With only 2 tools, the server feels under-scoped for a webcam domain, as it lacks operations like video capture, settings adjustment, or multi-camera support. This minimal set may limit agent functionality, making it borderline too few for comprehensive visual input handling.
The tool surface is significantly incomplete for a webcam server; it covers basic image capture from webcam and screen but misses essential operations such as starting/stopping video, configuring camera settings, or handling multiple inputs. This creates gaps that could lead to agent failures in more complex visual tasks.