Perceptron Vision MCP Server
OfficialClick on "Deploy 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., "@Perceptron Vision MCP ServerDescribe the image at https://example.com/photo.jpg"
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.
Perceptron Vision MCP Server
A vision MCP server by Perceptron — high-accuracy vision AI over the Model Context Protocol, powered by fast, efficient vision-language models.
Give any MCP-compatible agent direct access to Perceptron's Isaac model family for visual question answering, captioning, OCR, and object detection over images and videos.
Available Tools
Tool | Description |
| Visual question answering — ask a question about an image or video (requires |
| Captioning — generate concise or detailed descriptions of an image or video (requires |
| Text extraction — pull text from images as plain text, markdown, or HTML (image-only) |
| Object detection — locate and classify objects in an image or video, optionally filtered by class (requires |
| List available Perceptron models and their capabilities |
question, caption, and detect accept a URL (https://...), a local file path (/path/to/clip.mp4, ~/photos/image.png), or a base64 data URI (data:image/jpeg;base64,...) for images or videos, and require a modality parameter ("image" or "video"). ocr is image-only and uses an image_url parameter. Local files are automatically uploaded to the Perceptron platform before analysis. Currently supported formats: JPEG, PNG, WebP, MP4, and WebM.
Model Selection
The model parameter is optional — if omitted, the default Perceptron model is used. Call list_models to discover all available models and their capabilities.
Related MCP server: llm-vision-mcp
Configuration
Required
Variable | Description |
| Your Perceptron API key |
Get your API key from the Perceptron dashboard.
Optional
Variable | Default | Description |
|
| Custom API endpoint |
Installation
Claude Code
claude mcp add perceptron -e PERCEPTRON_API_KEY=your-api-key -- npx -y @perceptron-ai/mcp-server@latestClaude Desktop
Add to your Claude Desktop configuration file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"perceptron": {
"command": "npx",
"args": ["-y", "@perceptron-ai/mcp-server@latest"],
"env": {
"PERCEPTRON_API_KEY": "your-api-key"
}
}
}
}Cursor
Add to your Cursor MCP configuration (.cursor/mcp.json):
{
"mcpServers": {
"perceptron": {
"command": "npx",
"args": ["-y", "@perceptron-ai/mcp-server@latest"],
"env": {
"PERCEPTRON_API_KEY": "your-api-key"
}
}
}
}VS Code
Add to .vscode/mcp.json in your workspace:
{
"servers": {
"perceptron": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@perceptron-ai/mcp-server@latest"],
"env": {
"PERCEPTRON_API_KEY": "your-api-key"
}
}
}
}Windsurf
Add to your Windsurf MCP configuration (~/.codeium/windsurf/mcp_config.json):
{
"mcpServers": {
"perceptron": {
"command": "npx",
"args": ["-y", "@perceptron-ai/mcp-server@latest"],
"env": {
"PERCEPTRON_API_KEY": "your-api-key"
}
}
}
}Google Antigravity
Add to your Antigravity MCP configuration (~/.gemini/antigravity/mcp_config.json):
{
"mcpServers": {
"perceptron": {
"command": "npx",
"args": ["-y", "@perceptron-ai/mcp-server@latest"],
"env": {
"PERCEPTRON_API_KEY": "your-api-key"
}
}
}
}Codex
codex mcp add perceptron --env PERCEPTRON_API_KEY=your-api-key -- npx -y @perceptron-ai/mcp-server@latestGeneric MCP Clients
PERCEPTRON_API_KEY=your-api-key npx -y @perceptron-ai/mcp-server@latestNote: The @latest tag ensures you always get the newest models and tools. To pin a specific version, replace @latest with a version number from npm (e.g. @perceptron-ai/mcp-server@0.1.5).
How Local Files Work
When you pass a local file path as media_url (or image_url for ocr), the server transparently:
Reads the file from disk
Requests a presigned upload URL from the Perceptron platform
Uploads the file
Obtains a presigned download URL
Passes the download URL to the model for analysis
This means you can analyze images and videos on your machine without manual upload steps.
Troubleshooting
"PERCEPTRON_API_KEY environment variable is required"
Set the PERCEPTRON_API_KEY environment variable in your MCP client configuration.
"Unrecognized file extension"
The file extension could not be mapped to a MIME type. Rename the file with a standard extension (e.g. .jpg, .png, .webp).
Connection errors to the remote server
Verify your API key is valid and that you can reach https://api.perceptron.inc. If you need a custom endpoint, set PERCEPTRON_BASE_URL.
File not found errors
Ensure the file path is absolute or starts with ~. Relative paths are resolved from the server's working directory.
Development
# Install dependencies
npm install
# Run in development mode
PERCEPTRON_API_KEY=your-key npm run dev
# Build
npm run build
# Run tests
npm testLicense
This server cannot be deployed
Maintenance
Related MCP Connectors
OCR, transcription, file extraction, and image generation for AI agents via MCP.
MCP server for Clipkit — gives AI agents a video toolbox via the Clipkit schema.
MCP server for building and testing AI agents with multi-model experimentation and insights.
MCP server for Wan AI video generation
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