Perceptron Vision MCP Server

Perceptron Vision MCP Server

A vision MCP server that gives MCP-compatible agents direct access to Perceptron's Isaac model family for visual question answering, captioning, OCR, and object detection over images and videos.

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README

Perceptron Vision MCP Server

Install in Cursor   Install in VS Code   npm

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
question Visual question answering — ask a question about an image or video (requires modality)
caption Captioning — generate concise or detailed descriptions of an image or video (requires modality)
ocr Text extraction — pull text from images as plain text, markdown, or HTML (image-only)
detect Object detection — locate and classify objects in an image or video, optionally filtered by class (requires modality)
list_models 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.

Configuration

Required

Variable Description
PERCEPTRON_API_KEY Your Perceptron API key

Get your API key from the Perceptron dashboard.

Optional

Variable Default Description
PERCEPTRON_BASE_URL https://api.perceptron.inc Custom API endpoint

Installation

Claude Code

claude mcp add perceptron -e PERCEPTRON_API_KEY=your-api-key -- npx -y @perceptron-ai/mcp-server@latest

Claude 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@latest

Generic MCP Clients

PERCEPTRON_API_KEY=your-api-key npx -y @perceptron-ai/mcp-server@latest

Note: 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:

  1. Reads the file from disk
  2. Requests a presigned upload URL from the Perceptron platform
  3. Uploads the file
  4. Obtains a presigned download URL
  5. 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 test

License

Apache License 2.0

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