image-processing MCP Server

Image processing for AI agents. Resize, convert, compress, and pipeline images.

Tools

Last Updated

May 26, 2026

What is the image-processing MCP Server?

The image-processing MCP server gives AI agents structured, permission-aware access to image-processing through the Model Context Protocol. With 7 pre-built actions, agents can read, create, and update image-processing data on behalf of authorized users.

Willow ships the image-processing MCP server as part of an enterprise control plane. Every call runs behind SSO (Okta, Azure AD), enforces RBAC and least-privilege at runtime, writes to a full audit trail, and integrates with Splunk and Loki for SIEM visibility. Connect from Claude Desktop, Claude Code, Cursor, ChatGPT, VS Code, n8n, or any custom agent. Install once, distribute org-wide, and see exactly how image-processing is being used by every AI agent in your stack.

Tools

get_format_info

Get supported formats and options Returns supported output formats and their configurable options. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json

analyze_image

Analyze an image Fetch an image from a URL or base64 and return its metadata (size in bytes). Always free. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **Example Response:** ```json { "size_bytes": 1 } ```

resize_image

Resize an image Scale an image by a factor. Use 'scale' for uniform scaling, or 'scale_x'/'scale_y' for independent axes. Values are float factors (e.g. 0.5 = half size). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

compress_image

Compress an image Re-encode an image with quality/format options to reduce file size. Supports jpeg, png, webp, tiff, gif. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

convert_image

Convert image format Convert an image to a different format (jpeg, png, webp, tiff, gif). Optionally set quality, strip metadata, or enable lossless mode (webp). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

crop_image

Crop an image Extract a rectangular region from an image. Specify the top-left corner (x, y) and the dimensions (width, height) in pixels. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

image_pipeline

Run a multi-step image pipeline Chain multiple operations (resize, compress, convert, crop) in sequence. The image is fetched once, then each operation is applied to the output of the previous one. Max 10 operations per pipeline. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```

Customize Tools

Edit descriptions, modify arguments, select tools, or add new ones

Set Up Your image-processing MCP Server in Minutes

Add the following configuration to your MCP client. Authentication is handled via OAuth. Compatible with Claude Desktop, Claude Code, Cursor, ChatGPT, VS Code, n8n, and any MCP-compatible agent.

Claude Desktop

claude_desktop_config.json

{
  "mcpServers": {
    "willow-image-processing": {
      "type": "http",
      "url": "https://<org>.mcp-s.com/mcp/mcp/image-processing"
    }
  }
}

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "willow-image-processing": {
      "type": "http",
      "url": "https://<org>.mcp-s.com/mcp/mcp/image-processing"
    }
  }
}

Claude Code

CLI

claude mcp add willow-image-processing --transport http https://<org>.mcp-s.com/mcp/mcp/image-processing

n8n

HTTP Request Node

{
  "url": "https://<org>.mcp-s.com/mcp/mcp/image-processing",
  "method": "POST"
}

Or click "Install with Willow" above to set up automatically with SSO and RBAC preconfigured.

Enterprise Governance for image-processing

Willow adds the layer image-processing and every other SaaS doesn't ship out of the box: every call runs behind SSO (Okta, Azure AD), enforces RBAC and least-privilege at runtime, writes to full audit logs, and detects shadow AI usage across your stack. One MCP gateway. Any agent. Every tool.

image-processing MCP Server FAQ

What is the image-processing MCP server?

The image-processing MCP server is a Model Context Protocol implementation that lets AI agents like Claude, Cursor, and ChatGPT read and write image-processing data through a standardized interface. Willow hosts and governs this server so enterprises can roll it out without a security review backlog.

How is Willow's image-processing MCP server different from the official one?

The official image-processing MCP server is scoped to a single user's account and does not include enterprise governance. Willow's version adds SSO, RBAC, audit logging, shadow AI detection, and centralized control over which actions agents can take across the entire org.

Which AI clients work with the image-processing MCP server?

Claude Desktop, Claude Code, Cursor, ChatGPT, VS Code with MCP support, n8n, and any custom agent built with OpenAI Agents SDK, LangChain, Vercel AI SDK, or Anthropic SDK.

Is the image-processing MCP server secure? How does Willow handle authentication?

Every call runs behind your existing SSO (Okta, Azure AD). Per-user OAuth scopes the agent to exactly what that user can do in image-processing, nothing more. No credentials reach the LLM. Every action writes to an audit trail.

Can I limit which image-processing actions agents can take?

Yes. Willow lets you scope agents to specific actions, specific projects, or specific environments. Toggle actions on or off in the dashboard, or enforce policy via infrastructure-as-code through GitHub.

How do I detect shadow image-processing MCP servers in my org?

Willow's browser extension and discovery service surface unmanaged MCP servers, skills, and AI agents across the org. If a developer installed an unapproved image-processing MCP locally, you'll see it.

What does the image-processing MCP server cost?

Pricing depends on org size and deployment model (SaaS, dedicated cloud, self-host). See withwillow.ai/pricing or contact sales for a quote.

How do I install the image-processing MCP server with Willow?

Install via the Willow Connect Panel in one click, or paste the JSON snippet above into your Claude Desktop, Cursor, or Claude Code config. SSO and RBAC inherit from your existing Willow setup.