agent-vision-mcp
Provides image analysis capabilities using OpenAI-compatible vision APIs, enabling AI agents to analyze and describe images.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agent-vision-mcpAnalyze the image at /tmp/screenshot.png and describe what you see."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
agent-vision-mcp (hardened)
A hardened fork of @kitlau/agent-vision-mcp
— an MCP server that gives non-vision LLMs the ability to analyze images via any
OpenAI-compatible vision API (Claude Code, DeepSeek, etc.).
This build fixes intermittent empty / truncated image-analysis results and request hangs that affect long outputs (e.g. high-resolution 3D render screenshots) against self-hosted Qwen VLMs and similar backends.
What was broken upstream
The upstream package:
defaulted output
max_tokensto 1024 and never grew it, so long analyses hitfinish_reason: lengthand were cut off mid-sentence — and intermittently returned emptycontent, surfacing as❌ 视觉 API 返回的内容为空;only read
message.content, ignoringmessage.reasoning_contentused by Qwen3.x thinking-style models;had no retry on empty / 5xx / 429 / transient network errors;
set no client timeout, so slow high-res inference could hang and get killed (
MCP error -32001: user-cancel).
Related MCP server: image_mcp
What this build changes
dist/vision-client.js:
Grows
max_tokenson truncation (finish_reason === "length") and retries, so a low ceiling can never silently produce a partial/empty answer (grow ceiling: 32768).Falls back to
message.reasoning_contentwhencontentis empty (Qwen thinking mode).Retries on empty results, 5xx, 429, and network/timeout errors with exponential backoff (default 3 retries).
Sets an explicit client timeout (default 300000 ms) to prevent hangs.
dist/config.js:
Adds
VISION_MAX_TOKENS(default 16384),VISION_TIMEOUT_MS(default 300000),VISION_MAX_RETRIES(default 3) env vars, exposed on the config object.
Install as an MCP server
Point your MCP client at this repo. Example claude_desktop_config.json /
.mcp.json / global ~/.claude.json entry:
{
"mcpServers": {
"agent-vision": {
"type": "stdio",
"command": "node",
"args": ["path/to/this/repo/dist/index.js"]
}
}
}For a drop-in remote install, clone this repo and npm install, then run node dist/index.js.
Or add it as a dependency with npm install github:aabbccddwasd/agent-vision-mcp.
Environment variables
Variable | Default | Description |
| (required) | API key for the OpenAI-compatible endpoint |
|
| OpenAI-compatible base URL |
|
| The vision model, e.g. |
|
| Output token budget (was 1024 upstream) |
|
| Per-request client timeout |
|
| Retries for empty / 5xx / 429 / network errors |
|
| Optional disk response cache |
|
| Cache directory (when enabled) |
|
| Max image bytes (20 MB) |
License
MIT. Original author: kitlau86.
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
Tools
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- FlicenseNot gradedqualityCmaintenanceEnables text-only LLMs to process images by describing them through a configurable vision model.
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