Let Claude Code describe and reason about local image files on your computer during a conversation
Add image understanding to your Claude Code workflow using only Python's standard library
Connect Claude Code to the mimo-v2.5 vision API for image descriptions in an automated coding workflow
Requires a mimo-v2.5 API key and editing two Claude Code configuration files, no pip dependencies.
This repository contains a small Python server that acts as a bridge between Claude Code and a third-party image-understanding API called mimo-v2.5. The purpose is to let Claude Code read and describe local image files on your computer, something it cannot do on its own without this kind of connector. The way it works: when you ask Claude to look at an image, Claude calls a tool named describe_image that this server provides. The server reads the image file from your disk, encodes it, sends it to the mimo-v2.5 API, and returns a text description back to Claude. Claude then uses that description to continue the conversation. The API endpoint and authentication key are set in a configuration file, and the server runs in the background whenever Claude Code is open. Setup involves creating one Python file (about 250 lines) in a specific folder under your home directory, then editing two Claude configuration files to register the server. The README documents each file and each field in detail, with notes about Windows path formatting. After restarting Claude Code, the server loads automatically. To remove it, you delete the configuration entries from those two files and remove the folder. The README notes that uninstalling leaves no background processes or other residue. The README is written in Chinese and includes a troubleshooting table covering common errors such as a missing API key, a wrong file path, Python not being found, and a Windows character encoding issue that the server code already handles. It also includes brief notes on how the MCP protocol works: messages travel over standard input and output as JSON, and the server responds to a small set of method names for initialization, listing tools, and running tool calls. The server uses only Python's standard library with no external dependencies beyond the API calls it makes.
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