MCP Images MCP Server

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Local serverstdioPython

What is the MCP Images MCP server?

If you already use MCP Images, the mcp images mcp server is the piece that lets your assistant work with it directly. If you find this project helpful and would like to support future projects, consider buying us a coffee! Your support helps us continue building innovative AI solutions.

What the server does

  • Fetch images from URLs (http/https)
  • Load images from local file paths
  • Specialized handling for large local images
  • Automatic image compression for large images (>1MB)
  • Parallel processing of multiple images
  • Proper MIME type mapping for different file extensions

Available tools

The toolset is worth reading before you wire it up, because it tells you what the integration is really for:

  • Windsurf — 1. Edit the configuration file at ~/.codeium/windsurf/mcp_config.json 2. Add the following configuration: json { "mcpServers": { "image": {
  • Cursor — 1. Open Cursor and go to Settings (Navbar → Cursor Settings) 2. Navigate to FeaturesMCP Servers 3. Click on + Add New MCP Server 4. Enter
  • Examples — The Examples tool exposed by this server

Installation

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

Credentials and setup notes

  • Python 3.10+ - uv package manager (recommended)

Where it fits

Plenty of file and storage access servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. MCP Images's toolset — Windsurf, Cursor, Examples — is a fair guide to whether it matches your workflow. It is maintained by IA-Programming; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Worth knowing first

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Available tools

ToolWhat it does
Windsurf1. Edit the configuration file at ~/.codeium/windsurf/mcp_config.json 2. Add the following configuration: json { "mcpServers": { "image": { "command": "uv", "args": ["--directory", "/path/to/mcp-image", "run", "mcp_image
Cursor1. Open Cursor and go to *Settings* (Navbar → Cursor Settings) 2. Navigate to *Features* → *MCP Servers* 3. Click on + Add New MCP Server 4. Enter the following configuration: json { "mcpServers": { "image": { "command":
ExamplesThe Examples tool exposed by this server.

Configuration

  • Python 3.10+ - uv package manager (recommended)

Example prompts to try

  • Use MCP Images to Windsurf.
  • Use MCP Images to Cursor.
  • Use MCP Images to Examples.

Frequently asked questions

It connects MCP Images to MCP-compatible AI assistants such as Claude and Cursor, exposing 3 tools (Windsurf, Cursor, Examples) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP Images directly.