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: Vision MCP Server
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
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Tools
Related MCP Servers
- AlicenseAqualityDmaintenanceEnables image analysis and understanding using Vision Language Models through OpenAI-compatible APIs. Supports analyzing images from URLs or local files with custom prompts.Last updated12MIT
- AlicenseBqualityDmaintenanceEnables vision capabilities for any AI model by routing image analysis requests through OpenRouter's vision models. It provides tools to analyze images from URLs, local file paths, or base64 data.Last updated29117MIT
- Alicense-qualityDmaintenanceEnables text-only LLMs to analyze images by routing them to an OpenAI-compatible vision backend, supporting local files, URLs, and data URLs.Last updated53MIT
- AlicenseAqualityCmaintenanceEnables image analysis using any OpenAI-compatible vision API, supporting URLs, local files, or base64 input with custom prompts.Last updated1MIT
Related MCP Connectors
OCR, transcription, file extraction, and image generation for AI agents via MCP.
Zero-auth MCP: image optimize, cited storage/format data, and dev utilities LLMs get wrong.
Analyze images from multiple angles to extract detailed insights or quick summaries. Describe visu…
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/aabbccddwasd/agent-vision-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server