⭐⭐ 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/. You can specify your own UserID by adding ?user= 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.

!mcp_webcam_020_thumb

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.

!image

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.

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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

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Install a recent version of NodeJS 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.

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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:

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Start the mcp-webcam in streaming mode, install 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"]
`

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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.

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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 for more details about handling files and resources in LLM / MCP Chat Applications, and why you might want to do this.