Advertise
MCP.so
Sign In

Snap Sense MCP Server

@Abhi5h3k

Repository

Basic information

Category

Other

Transports

stdio

Author

Abhi5h3k

Submitted by

Abhishek Bhardwaj

About Snap Sense MCP Server

Demo MCP tool to capture URL screenshot.

#snap-sense#mcp#screenshot-capture

Snap Sense MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "snap_sense": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/PARENT/FOLDER/weather",
        "run",
        "server.py"
      ],
      "env": {
        "ABSTRACT_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Snap Sense MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Snap_sense?

Snap_sense is a lightweight Model Context Protocol (MCP) server that enables your LLM to capture screenshots of any specified URL and return only the access URL for the captured image. It is built with Python and the MCP SDK, designed for integrating visual capture capabilities into AI applications like Claude Desktop or automation workflows.

How to use Snap_sense?

Install via Smithery (npx -y @smithery/cli install @Abhi5h3k/MCP-URL2SNAP --client claude) or manually: clone the repository, set up a Python virtual environment (Python 3.11+, UV 0.6.9+), install dependencies with uv install, create a .env file with your ABSTRACT_API_KEY, and run uv run server.py. Register the server in Claude Desktop's claude_desktop_config.json using the uv command and restart Claude. Then prompt with requests like "can you show me the screenshot of https://example.com".

Key features of Snap_sense

  • Lightweight MCP server for capturing webpage screenshots
  • Returns only the access URL of the captured image
  • Seamless integration with MCP-compatible LLMs
  • Easy setup with Python and the MCP SDK
  • Configurable via environment variable (AbstractAPI key)

Use cases of Snap_sense

  • Enabling AI assistants like Claude Desktop to capture and share webpage snapshots on demand
  • Automating screenshot generation for website monitoring or reporting workflows
  • Integrating visual capture into custom MCP-based automation pipelines

Frequently asked questions

1

What dependencies are required to run Snap_sense?

The server requires Python 3.11.0 or higher and UV 0.6.9 or higher. All other dependencies are installed automatically via UV.

2

How is the screenshot captured and stored?

Snap_sense uses the AbstractAPI Screenshot API (accessed via your `ABSTRACT_API_KEY`) to capture the screenshot. The server returns only the access URL for the hosted image; the image itself is stored by AbstractAPI.

3

What transport and authentication does Snap_sense use?

The server communicates via the MCP protocol over standard I/O (stdio). Authentication to the screenshot service is provided through the `ABSTRACT_API_KEY` environment variable.

4

Can Snap_sense be used with any MCP-compatible client?

Yes, the README demonstrates integration with Claude Desktop via the `claude_desktop_config.json` file, and the server is designed to work with any MCP-compatible LLM or client that supports the protocol.

Comments

More Other MCP servers

Volley.sh

Volley

A good sequence diagram can solve almost any communication problem in engineering. Volley lets your agent write them as plain text, with the real request and response payloads on every arrow. It checks its own syntax wi

EverArt

modelcontextprotocol

Model Context Protocol Servers

88.1K

Blender

ahujasid

Open-source MCP to use Blender with any LLM

23.6K

YOUB

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov

Sequential Thinking

modelcontextprotocol

Model Context Protocol Servers

88.2K
Advertise